{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.model_selection import cross_val_score, GridSearchCV, train_test_split\n",
    "from sklearn.linear_model import Lasso, LogisticRegression\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import accuracy_score, roc_auc_score, roc_curve\n",
    "\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>action_type</th>\n",
       "      <th>combined_shot_type</th>\n",
       "      <th>lat</th>\n",
       "      <th>loc_x</th>\n",
       "      <th>loc_y</th>\n",
       "      <th>lon</th>\n",
       "      <th>minutes_remaining</th>\n",
       "      <th>period</th>\n",
       "      <th>playoffs</th>\n",
       "      <th>season</th>\n",
       "      <th>seconds_remaining</th>\n",
       "      <th>shot_distance</th>\n",
       "      <th>shot_made_flag</th>\n",
       "      <th>shot_type</th>\n",
       "      <th>shot_zone_area</th>\n",
       "      <th>shot_zone_basic</th>\n",
       "      <th>shot_zone_range</th>\n",
       "      <th>game_date</th>\n",
       "      <th>matchup</th>\n",
       "      <th>opponent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shot_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>33.9723</td>\n",
       "      <td>167</td>\n",
       "      <td>72</td>\n",
       "      <td>-118.1028</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>27</td>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Right Side(R)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>34.0443</td>\n",
       "      <td>-157</td>\n",
       "      <td>0</td>\n",
       "      <td>-118.4268</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>22</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Left Side(L)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>8-16 ft.</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>33.9093</td>\n",
       "      <td>-101</td>\n",
       "      <td>135</td>\n",
       "      <td>-118.3708</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>45</td>\n",
       "      <td>16</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Left Side Center(LC)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>33.8693</td>\n",
       "      <td>138</td>\n",
       "      <td>175</td>\n",
       "      <td>-118.1318</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>52</td>\n",
       "      <td>22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Right Side Center(RC)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Driving Dunk Shot</td>\n",
       "      <td>Dunk</td>\n",
       "      <td>34.0443</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-118.2698</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Center(C)</td>\n",
       "      <td>Restricted Area</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               action_type combined_shot_type      lat  loc_x  loc_y  \\\n",
       "shot_id                                                                \n",
       "1                Jump Shot          Jump Shot  33.9723    167     72   \n",
       "2                Jump Shot          Jump Shot  34.0443   -157      0   \n",
       "3                Jump Shot          Jump Shot  33.9093   -101    135   \n",
       "4                Jump Shot          Jump Shot  33.8693    138    175   \n",
       "5        Driving Dunk Shot               Dunk  34.0443      0      0   \n",
       "\n",
       "              lon  minutes_remaining period playoffs   season  \\\n",
       "shot_id                                                         \n",
       "1       -118.1028                 10      1        0  2000-01   \n",
       "2       -118.4268                 10      1        0  2000-01   \n",
       "3       -118.3708                  7      1        0  2000-01   \n",
       "4       -118.1318                  6      1        0  2000-01   \n",
       "5       -118.2698                  6      2        0  2000-01   \n",
       "\n",
       "         seconds_remaining  shot_distance shot_made_flag       shot_type  \\\n",
       "shot_id                                                                    \n",
       "1                       27             18            NaN  2PT Field Goal   \n",
       "2                       22             15            0.0  2PT Field Goal   \n",
       "3                       45             16            1.0  2PT Field Goal   \n",
       "4                       52             22            0.0  2PT Field Goal   \n",
       "5                       19              0            1.0  2PT Field Goal   \n",
       "\n",
       "                shot_zone_area  shot_zone_basic  shot_zone_range   game_date  \\\n",
       "shot_id                                                                        \n",
       "1                Right Side(R)        Mid-Range        16-24 ft.  2000-10-31   \n",
       "2                 Left Side(L)        Mid-Range         8-16 ft.  2000-10-31   \n",
       "3         Left Side Center(LC)        Mid-Range        16-24 ft.  2000-10-31   \n",
       "4        Right Side Center(RC)        Mid-Range        16-24 ft.  2000-10-31   \n",
       "5                    Center(C)  Restricted Area  Less Than 8 ft.  2000-10-31   \n",
       "\n",
       "           matchup opponent  \n",
       "shot_id                      \n",
       "1        LAL @ POR      POR  \n",
       "2        LAL @ POR      POR  \n",
       "3        LAL @ POR      POR  \n",
       "4        LAL @ POR      POR  \n",
       "5        LAL @ POR      POR  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kobe = pd.read_csv('Kobe.csv')\n",
    "\n",
    "# Для удобства категориальные переменные переведем в тип category\n",
    "\n",
    "df_kobe.set_index('shot_id', inplace=True)\n",
    "df_kobe[\"action_type\"] = df_kobe[\"action_type\"].astype('object')\n",
    "df_kobe[\"combined_shot_type\"] = df_kobe[\"combined_shot_type\"].astype('category')\n",
    "df_kobe[\"game_event_id\"] = df_kobe[\"game_event_id\"].astype('category')\n",
    "df_kobe[\"game_id\"] = df_kobe[\"game_id\"].astype('category')\n",
    "df_kobe[\"period\"] = df_kobe[\"period\"].astype('object')\n",
    "df_kobe[\"playoffs\"] = df_kobe[\"playoffs\"].astype('category')\n",
    "df_kobe[\"season\"] = df_kobe[\"season\"].astype('category')\n",
    "df_kobe[\"shot_made_flag\"] = df_kobe[\"shot_made_flag\"].astype('category')\n",
    "df_kobe[\"shot_type\"] = df_kobe[\"shot_type\"].astype('category')\n",
    "df_kobe[\"team_id\"] = df_kobe[\"team_id\"].astype('category')\n",
    "\n",
    "# Удаляем ненужные признаки\n",
    "df_kobe.drop('team_id', axis=1, inplace=True) # Всегда один и тот же номер\n",
    "df_kobe.drop('game_id', axis=1, inplace=True) # Независимый признак\n",
    "df_kobe.drop('game_event_id', axis=1, inplace=True) # Независимый признак\n",
    "df_kobe.drop('team_name', axis=1, inplace=True) # Везде одна и та же команда\n",
    "\n",
    "df_kobe[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Визуализация данных\n",
    "\n",
    "Проверим наличие пропущенных значений в признаках"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Статистика пропущенных значений:\n",
      "\n",
      "action_type: 0.0%\n",
      "combined_shot_type: 0.0%\n",
      "lat: 0.0%\n",
      "loc_x: 0.0%\n",
      "loc_y: 0.0%\n",
      "lon: 0.0%\n",
      "minutes_remaining: 0.0%\n",
      "period: 0.0%\n",
      "playoffs: 0.0%\n",
      "season: 0.0%\n",
      "seconds_remaining: 0.0%\n",
      "shot_distance: 0.0%\n",
      "shot_made_flag: 16.29%\n",
      "shot_type: 0.0%\n",
      "shot_zone_area: 0.0%\n",
      "shot_zone_basic: 0.0%\n",
      "shot_zone_range: 0.0%\n",
      "game_date: 0.0%\n",
      "matchup: 0.0%\n",
      "opponent: 0.0%\n"
     ]
    }
   ],
   "source": [
    "print('Статистика пропущенных значений:\\n')\n",
    "for colname in df_kobe.columns:\n",
    "    stat = df_kobe[colname].isna().mean() * 100\n",
    "    print(f'{colname}: {round(stat, 2)}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Типы данных в признаках датасета:\n",
      "\n",
      "action_type             object\n",
      "combined_shot_type    category\n",
      "lat                    float64\n",
      "loc_x                    int64\n",
      "loc_y                    int64\n",
      "lon                    float64\n",
      "minutes_remaining        int64\n",
      "period                  object\n",
      "playoffs              category\n",
      "season                category\n",
      "seconds_remaining        int64\n",
      "shot_distance            int64\n",
      "shot_made_flag        category\n",
      "shot_type             category\n",
      "shot_zone_area          object\n",
      "shot_zone_basic         object\n",
      "shot_zone_range         object\n",
      "game_date               object\n",
      "matchup                 object\n",
      "opponent                object\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(f'Типы данных в признаках датасета:\\n\\n{df_kobe.dtypes}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Проверим корреляцию между признаками"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df_kobe.corr(method='spearman').apply(np.abs))\n",
    "plt.title(\"Тепловая карта корреляций между численными признаками\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Как видно из тепловой карты у нас сильно крррелируют между собой lat и loc_y, lon и loc_x.\n",
    "\n",
    "Посмотрим на стандартные статистчиеские метрики (медиана, СКО и др.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lat</th>\n",
       "      <th>loc_x</th>\n",
       "      <th>loc_y</th>\n",
       "      <th>lon</th>\n",
       "      <th>minutes_remaining</th>\n",
       "      <th>seconds_remaining</th>\n",
       "      <th>shot_distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>33.953192</td>\n",
       "      <td>7.110499</td>\n",
       "      <td>91.107535</td>\n",
       "      <td>-118.262690</td>\n",
       "      <td>4.885624</td>\n",
       "      <td>28.365085</td>\n",
       "      <td>13.437437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.087791</td>\n",
       "      <td>110.124578</td>\n",
       "      <td>87.791361</td>\n",
       "      <td>0.110125</td>\n",
       "      <td>3.449897</td>\n",
       "      <td>17.478949</td>\n",
       "      <td>9.374189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>33.253300</td>\n",
       "      <td>-250.000000</td>\n",
       "      <td>-44.000000</td>\n",
       "      <td>-118.519800</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>33.884300</td>\n",
       "      <td>-68.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>-118.337800</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>33.970300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>-118.269800</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>34.040300</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>-118.174800</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>21.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>34.088300</td>\n",
       "      <td>248.000000</td>\n",
       "      <td>791.000000</td>\n",
       "      <td>-118.021800</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>79.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                lat         loc_x         loc_y           lon  \\\n",
       "count  30697.000000  30697.000000  30697.000000  30697.000000   \n",
       "mean      33.953192      7.110499     91.107535   -118.262690   \n",
       "std        0.087791    110.124578     87.791361      0.110125   \n",
       "min       33.253300   -250.000000    -44.000000   -118.519800   \n",
       "25%       33.884300    -68.000000      4.000000   -118.337800   \n",
       "50%       33.970300      0.000000     74.000000   -118.269800   \n",
       "75%       34.040300     95.000000    160.000000   -118.174800   \n",
       "max       34.088300    248.000000    791.000000   -118.021800   \n",
       "\n",
       "       minutes_remaining  seconds_remaining  shot_distance  \n",
       "count       30697.000000       30697.000000   30697.000000  \n",
       "mean            4.885624          28.365085      13.437437  \n",
       "std             3.449897          17.478949       9.374189  \n",
       "min             0.000000           0.000000       0.000000  \n",
       "25%             2.000000          13.000000       5.000000  \n",
       "50%             5.000000          28.000000      15.000000  \n",
       "75%             8.000000          43.000000      21.000000  \n",
       "max            11.000000          59.000000      79.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kobe.describe(include=['float64', 'int64'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>action_type</th>\n",
       "      <th>combined_shot_type</th>\n",
       "      <th>period</th>\n",
       "      <th>playoffs</th>\n",
       "      <th>season</th>\n",
       "      <th>shot_made_flag</th>\n",
       "      <th>shot_type</th>\n",
       "      <th>shot_zone_area</th>\n",
       "      <th>shot_zone_basic</th>\n",
       "      <th>shot_zone_range</th>\n",
       "      <th>game_date</th>\n",
       "      <th>matchup</th>\n",
       "      <th>opponent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>25697.0</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>57</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1559</td>\n",
       "      <td>74</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2005-06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Center(C)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>2016-04-13</td>\n",
       "      <td>LAL @ SAS</td>\n",
       "      <td>SAS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>18880</td>\n",
       "      <td>23485</td>\n",
       "      <td>8296</td>\n",
       "      <td>26198</td>\n",
       "      <td>2318</td>\n",
       "      <td>14232.0</td>\n",
       "      <td>24271</td>\n",
       "      <td>13455</td>\n",
       "      <td>12625</td>\n",
       "      <td>9398</td>\n",
       "      <td>50</td>\n",
       "      <td>1020</td>\n",
       "      <td>1978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       action_type combined_shot_type  period  playoffs   season  \\\n",
       "count        30697              30697   30697     30697    30697   \n",
       "unique          57                  6       7         2       20   \n",
       "top      Jump Shot          Jump Shot       3         0  2005-06   \n",
       "freq         18880              23485    8296     26198     2318   \n",
       "\n",
       "        shot_made_flag       shot_type shot_zone_area shot_zone_basic  \\\n",
       "count          25697.0           30697          30697           30697   \n",
       "unique             2.0               2              6               7   \n",
       "top                0.0  2PT Field Goal      Center(C)       Mid-Range   \n",
       "freq           14232.0           24271          13455           12625   \n",
       "\n",
       "        shot_zone_range   game_date    matchup opponent  \n",
       "count             30697       30697      30697    30697  \n",
       "unique                5        1559         74       33  \n",
       "top     Less Than 8 ft.  2016-04-13  LAL @ SAS      SAS  \n",
       "freq               9398          50       1020     1978  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kobe.describe(include=['object', 'category'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сильных выбросов в данных не наблюдается. loc_x и loc_y имеют большое СКО, эти признаки преобразуем в категориальные с помощью бинов.\n",
    "\n",
    "Проверим распределение по целевой переменной."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\formats\\format.py:1403: FutureWarning: Index.ravel returning ndarray is deprecated; in a future version this will return a view on self.\n",
      "  for val, m in zip(values.ravel(), mask.ravel())\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='shot_made_flag', data=df_kobe)\n",
    "plt.title('Распределение образцов по целевому значению')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Явного дисбаланса не наблюдается, поэтому оставим данные как есть."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Подготовка данных и создание признаков"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kobe.drop('lat', axis=1, inplace=True) # Сильно коорелирует с loc_x\n",
    "df_kobe.drop('lon', axis=1, inplace=True) # Сильно коррелирует с loc_y\n",
    "\n",
    "# Могут иметь значения последние 5 секунд до окончания игры, так как человек может играть более активно и идти на риски.\n",
    "# Нам важно узнать было попадание или промах почти в конце раунда или нет\n",
    "df_kobe['seconds_from_period_end'] = 60 * df_kobe['minutes_remaining'] + df_kobe['seconds_remaining']\n",
    "df_kobe['last_5_sec_in_period'] = df_kobe['seconds_from_period_end'] < 5\n",
    "\n",
    "df_kobe.drop('minutes_remaining', axis=1, inplace=True)\n",
    "df_kobe.drop('seconds_remaining', axis=1, inplace=True)\n",
    "df_kobe.drop('seconds_from_period_end', axis=1, inplace=True)\n",
    "\n",
    "## Разделяем игру на гостевую и домашнюю\n",
    "df_kobe['home_play'] = df_kobe['matchup'].str.contains('vs').astype('int')\n",
    "df_kobe.drop('matchup', axis=1, inplace=True)\n",
    "\n",
    "# разбиваем дату на год, месяц и день\n",
    "df_kobe['game_date'] = pd.to_datetime(df_kobe['game_date'])\n",
    "df_kobe['game_year'] = df_kobe['game_date'].dt.year\n",
    "df_kobe['game_month'] = df_kobe['game_date'].dt.month\n",
    "df_kobe.drop('game_date', axis=1, inplace=True)\n",
    "\n",
    "# Конвертируем непрерывные значения loc_x и loc_y в категориальные бины\n",
    "df_kobe['loc_x'] = pd.cut(df_kobe['loc_x'], 25)\n",
    "df_kobe['loc_y'] = pd.cut(df_kobe['loc_y'], 25)\n",
    "\n",
    "# Заменим 20 самых непопулярных типов действий на тип 'Other', так их количество очень мало\n",
    "rare_action_types = df_kobe['action_type'].value_counts().sort_values().index.values[:20]\n",
    "df_kobe.loc[df_kobe['action_type'].isin(rare_action_types), 'action_type'] = 'Other'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "categorial_cols = [\n",
    "    'action_type', 'combined_shot_type', 'period', 'season', 'shot_type',\n",
    "    'shot_zone_area', 'shot_zone_basic', 'shot_zone_range', 'game_year',\n",
    "    'game_month', 'opponent', 'loc_x', 'loc_y']\n",
    "df_kobe = pd.get_dummies(df_kobe, columns=categorial_cols)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Построим модель логистической регресси с L1- и L2-регуляризацией. Будем использовать разный размер коэффициента регуляризации, чттобы посмотреть влияние на размер весов и их обнуление.\n",
    "\n",
    "Возьмем логистическую регрессию и будем изменять тип регуляризации и коэффициент С. При С = 1.0 регуляризация "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kobe = df_kobe[~df_kobe.shot_made_flag.isna()]\n",
    "X = df_kobe[df_kobe.columns.drop('shot_made_flag')]\n",
    "y = df_kobe['shot_made_flag']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_l1 = pd.DataFrame()\n",
    "c_values = np.linspace(0.001, 1, 40)\n",
    "for c_value in c_values:\n",
    "    c_value = round(c_value, 3)\n",
    "    lr_l1 = LogisticRegression(penalty='l1', C=c_value, solver='liblinear')\n",
    "    lr_l1.fit(X, y)\n",
    "    df_l1['C_' + str(c_value)] = pd.Series(lr_l1.coef_[0])\n",
    "df_l1.index = X.columns.to_list()\n",
    "\n",
    "df_l2 = pd.DataFrame()\n",
    "for c_value in c_values:\n",
    "    c_value = round(c_value, 3)\n",
    "    lr_l2 = LogisticRegression(penalty='l2', C=c_value, solver='liblinear')\n",
    "    lr_l2.fit(X, y)\n",
    "    df_l2['C_' + str(c_value)] = pd.Series(lr_l2.coef_[0])\n",
    "df_l2.index = X.columns.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PWWTZ31U5w3pT92mrY8l+CbxM1gnw6znDegK/r++0GEBk/Vfet2NExP1puX8l6yw9ktTHI7Lz0x8lO4+8gKwfyoH1LSfHHpLmSppLdsrorDynO4nsVMdOEbGU7ED5TbKd/1vAxyJiCdkvwBOAIyNibT3zez4iHspz2cA79T6YbD3MI6v7z4HqBOdsst78z5A1O/6c/FsOX0jbwEPATyJiSkRMJ+t78gRZy8EuZFchbI2/kZq7q085SBpN1hpzdtTdd+s4si+a6WTNxbeRdYSvtk+KfwVZ58TTc4YNzPnMf0yNX+nKOvf+lqxD++qI+AswiVo68Of4VlreAlLn9lT+O7IWg3skrSLb5/aCrLWArKPsN8k+n8nA+DTdGWTn4F8nS5r/QpbM5lO/XFeT/cp8BJhJ1hp4Rj31qFUDsdanzvrnscxJZP1+Lib7jCvJktEtsSX71YK0nHlkyd6p6csashbXH6Y6nMd7f63uAjyfhj1O9mOo5i97IuKciKjtCy6fdfQwWf3vJ2tlvCeVn02WiK0iSxZvpvF+S8PfDdeRtTIuIGt1rG5t+zPZ6aE3yfbJmq0T79jK9VCffwDPkm2b/+bd760fkHVZWJHKb2/svCLib2T79k3p+3Uq9V/AkmuLj3XKOi7/kazv5sp6Yv0C2bZ7LPDpeLc/KmTfSTW7kUDWQvRwWtfTyI4Pv0zD8tmuHs05jp4JfE6pb3EDy622xd952rLGAbOWTdIMsqbk+4odi7VNyq5evT4iaruwoGiUXdAxE+jQiNa6QsfyENk6qtlXp+gkBdkpmsqWNK9a5l3QY52k88kuGf9SIea3lbF8GRgeEec31TK29CoNsxZL0mfITt080NC4ZmatVRs41s3j3b7FTcLJj5WE9EtyNNll5E2605iZFUtbONblnIptMj7tZWZmZm1KYy51NzMzM2u1fNqrxPXt2zeGDx9e7DDMzFqVZ599dklE1HXbB2vlnPyUuOHDhzNp0qRih2Fm1qpIqusGulYCfNrLzMzM2hQnP2ZmZtamOPkxMzOzNsXJj5mZmbUpTn7MzMysTXHyY2ZmZm2Kkx8zMzNrU5z8WK2mz1vJBf+ezvpNm4sdipmZWUE5+bFazV66hj8+OpOX5q8qdihmZmYF5eTHajW+ohyAF+YsL2ocZmZmhebkx2o1qFdn+nbvxAtzlxc7FDMzs4Jy8mO1ksSEil5u+TEzs5Lj5MfqNG5oOa8vWcPKdRuLHYqZmVnBOPmxOo2vKCcCps5dUexQzMzMCsbJTxFJqpD0oKSXJE2TdFYq7yPpXkmvpf+9c6Y5V1KlpFckHdKU8Y0f2guAF5z8mJlZCXHyU1ybgG9GxChgb+A0SaOB7wD3R8QOwP3pPWnYUcAY4FDgUkllTRVcedeObLtNV/f7MTOzkuLkp4giYn5EPJderwJeAoYARwLXptGuBT6ZXh8J3BQR6yNiJlAJ7NmUMY4fWu4rvszMrKQ4+WkhJA0HdgWeAgZExHzIEiSgfxptCDAnZ7K5qazmvE6RNEnSpMWLF29VXOOG9mL+inUsWrluq+ZjZmbWUjj5aQEkdQf+Cnw9IlbWN2otZfG+gogrImJiREzs16/fVsU2ofpmh+73Y2ZmJcLJT5FJ6kCW+NwQEben4oWSBqXhg4BFqXwuUJEz+VBgXlPGN2ZwL8raiSk+9WVmZiXCyU8RSRJwFfBSRPw6Z9AdwPHp9fHAP3LKj5LUSdJ2wA7A000ZY5eOZew4oAeT3enZzMxKRPtiB9DGfQA4FnhR0uRU9l3gZ8Atkk4E3gA+BxAR0yTdAkwnu1LstIho8seuT6joxZ0vLiAiyPI1MzOz1svJTxFFxGPU3o8H4CN1THMBcEGTBVWLcUPLufHpOcxeupbhfbs156LNzMwKzqe9rEHjh5YD+JJ3MzMrCU5+rEE7DuhO5w7teGGOr/gyM7PWz8mPNah9WTvGDu7llh8zMysJTn4sL+Mrypk2bwUbN1cVOxQzM7Ot4uTH8jJuaC/Wbazi1YWrih2KmZnZVnHyY3mpvtPzFN/p2czMWjknP5aXYX26Ut61g5/wbmZmrZ6TH8uLJMYNLfczvszMrNVz8mN5mzC0F68uXMXaDZuKHYqZmVmjOfmxvI0bWs7mqmDavPoePG9mZtayOfmxvI2r6AXgfj9mZtaqOfmxvPXv0ZnBvTq734+ZmbVqTn5si4yvKGeK7/RsZmatmJMf2yLjK8qZvXQtb63ZUOxQzMzMGsXJj22RcUOzfj9T3vSpLzMza52c/NgW2WVILyR3ejYzs9bLyU8RSbpa0iJJU3PKJkh6UtJkSZMk7Zkz7FxJlZJekXRIMWLu0bkDI/t1d/JjZmatlpOf4roGOLRG2S+AH0TEBOC89B5Jo4GjgDFpmksllTVbpDnGpzs9R0QxFm9mZrZVnPwUUUQ8AiyrWQz0TK97AfPS6yOBmyJifUTMBCqBPSmC8RW9WLJ6PfNWrCvG4s3MzLZK+2IHYO/zdeBuSReSJaf7pvIhwJM5481NZe8j6RTgFIBhw4YVPMDxQ8sBmDJnOUPKuxR8/mZmZk3JLT8tz9eAb0REBfAN4KpUrlrGrfW8U0RcERETI2Jiv379Ch7gzoN60LGsHZN9vx8zM2uFnPy0PMcDt6fXt/Luqa25QEXOeEN595RYs+rUvoxRg3owZY4vdzczs9bHyU/LMw/YP73+MPBaen0HcJSkTpK2A3YAni5CfMC7d3reXOVOz2Zm1ro4+SkiSTcCTwA7SZor6UTgZOBXkl4AfkLquxMR04BbgOnAXcBpEbG5OJHDhIpy1mzYTOWi1cUKwczMrFHc4bmIIuLoOgbtXsf4FwAXNF1E+ZtQUQ7A5DlvsdPAHsUNxszMbAu45ccaZbu+3ejVpQPPv7G82KGYmZltESc/1iiSmFBRzmTf6dnMzFoZJz/WaBMqynl14SpWr99U7FDMzMzy5uSnACR1kTQ2vT5K0umSejY0XWu367ByqgKm+H4/ZmbWirjDc2H8HRggaQGwCFhFdo+eojx8tLm82+l5OfuO7FvcYMzMzPLk5KcwKoCxwJyIGAKQLlUvaeVdOzKibzd3ejYzs1bFp70KYyNQDiyV1FtSnyLH02yqOz37Ce9mZtZaOPkpjF7As0AP4Lmc1yVvwrByFq9az5vL3y52KGZmZnnxaa8CiIjhxY6hWHat6A1k/X6G9u5a5GjMzMwa5pafApDUQdKZkm5Lf6dL6lDsuJrDzoN60Kl9Oya734+ZmbUSbvkpjMuADsCl6f2xqeykokXUTDqUtWOXIb143jc7NDOzVsLJT2HsERHjc94/0Bau9qo2oaKc656czYZNVXRs78ZEMzNr2fxNVRibJY2sfiNpBFC0J643t12H9Wb9pipeXrCy2KGYmZk1yC0/hXEO8KCk1wEB2wInFDek5jNhWDmQdXoeN7S8qLGYmZk1xMlPAUTE/ZJ2AHYiS35ejoj1RQ6r2Qzu1Zl+PTrx/BvLOW6fYkdjZmZWP5/2KgBJpwFdImJKRLwAdJX0P8WOq7lIYlc/4d3MzFoJJz+FcXJELK9+ExFvASc3NJGkqyUtkjS1RvkZkl6RNE3SL3LKz5VUmYa1qOeGTRhWzswla3hrzYZih2JmZlYvJz+F0U6Sqt9IKgM65jHdNcChuQWSDgSOBMZFxBjgwlQ+GjgKGJOmuTQtp0V452aHfsK7mZm1cE5+CuNu4BZJH5H0YeBG4K6GJoqIR4BlNYq/Bvysus9QRCxK5UcCN0XE+oiYCVQCexaqAltr3NBetBO+2aGZmbV4Tn4K49vAA2SJy2nA/cC3GjmvHYEPSnpK0sOS9kjlQ4A5OePNTWXvI+kUSZMkTVq8eHEjw9gy3Tq1Z8cBPXyzQzMza/F8tVcBRESVpGuAByLila2cXXugN7A3sAdZi9IIsqvI3rfoOuK5ArgCYOLEic32uPVdh5Vz54sLqKoK2rWrLVwzM7Pic8tPAUj6BDCZdKpL0gRJdzRydnOB2yPzNFAF9E3lFTnjDQXmNTroJjChopwVb29k5tI1xQ7FzMysTk5+CuP7ZP1vlgNExGRgeCPn9XfgwwCSdiTrOL0EuAM4SlInSdsBOwBPb0XMBbfrsNTp2f1+zMysBXPyUxibImLFlk4k6UbgCWAnSXMlnQhcDYxIl7/fBByfWoGmAbcA08lamE6LiBb1CI2R/brTvVN73+/HzMxaNPf5KYypko4BytKdns8EHm9ooog4uo5BX6pj/AuACxodZRMrayfGDe3F83PeKnYoZmZmdXLLT2GcQXb/nfVkl7mvBL5ezICKZddh5bw8fxVvb2hRjVJmZmbvcMtPAUTEWuB76a9Nm1DRm01VwdR5K9hjeJ9ih2NmZvY+bvkpAElfkHRbusnhy+mRFbWeuip1EyrKAXd6NjOzlsvJT2H8iKxz8l+BjwHjgHOLGlGR9OvRiaG9u7jfj5mZtVhOfgpjTUTcBsyOiMqIWEDW/6dNmlBR7pYfMzNrsZz8FMYQSb8HBkn6vaSLqOPRE23BrsN6M2/FOhauXFfsUMzMzN7HHZ4L45z0/9mcsknFCKQlqO738/wbyzl07MDiBmNmZlaDk58CiIhrix1DSzJmcE86lInJc5z8mJlZy+PTXlZwnTuUMXpwL56eubTYoZiZmb2Pkx9rEh/eqT/Pz1nufj9mZtbiOPkpAEmdaynrW4xYWoojxg0kAu6auqDYoZiZmb2Hk5/CeEbS3tVvJH2GPJ7tVcq279+DHfp3584X5xc7FDMzs/dwh+fCOAa4WtJDwGBgG+DDRY2oBTh8l0H8/oHXWLRqHf17vK9xzMzMrCjc8lMAEfEi2dPWTwUOBE6PiLnFjar4Dt9lEBFwt099mZlZC+LkpwAkXUX2FPdxwAnAPyWdVtSgWoAdB3RnZL9u3Pmikx8zM2s5nPwUxlTgwIiYGRF3A3sDuzU0kaSr00NQp9Yy7GxJkdtxWtK5kiolvSLpkILWoAlI4ohdBvHUzKUsWd1mn/ZhZmYtjJOfAoiI30RE5LxfEREn5jHpNcChNQslVQAfBd7IKRsNHAWMSdNcKqlsK0NvcoftMoiqgLunufXHzMxaBic/BSBppqTXc/5mSnq9oeki4hFgWS2DfgN8C4icsiOBmyJifUTMBCqBPQsRf1PaeWAPRvTt5qu+zMysxfDVXoUxMed1V6AMWNWYGUn6BPBmRLwgKXfQEODJnPdzaQUPT5XEYbsM5LKHZrB09Xq26d6p2CGZmVkb55afAoiIpRGxFPg48BzZPX5O2NL5SOoKfA84r7bBtS26jvmcImmSpEmLFy/e0jAK7vB06uue6QuLHYqZmZmTnwI7A9gZ2A44uhHTj0zTviBpFjAUeE7SQLKWnoqccYcC82qbSURcERETI2Jiv379GhFGYY0e1JNtt+nqU19mZtYiOPkpLKVWoPXAmi2dOCJejIj+ETE8IoaTJTy7RcQC4A7gKEmdJG0H7AA8Xcjgm4okDt9lEI/PWMpbazYUOxwzM2vjnPwUgKR/SroDGCHpDkn/BEbnMd2NwBPATpLmSqrzCrGImAbcAkwH7gJOi4jNhalB0ztil0Fsrgrume6rvszMrLjc4bkwLkz/f7UlE0VEvafGUutP7vsLyO4k3eqMGdyTij5duPPFBXxhj2HFDsfMzNowJz8FEBEPV7+WNAToHRHvu3FhW1Z96uuqR2eyfO0Gyrt2LHZIZmbWRvm0VwFI+mW6U/P3gHuAGyT9pthxtTSHjx3EpqrwVV9mZlZUbvkpjE8BY4FXgEHARmBKUSNqgcYN7cXQ3l34z4vz+fzEioYnMDMzawJu+SmMlRGxCJgVEetSR2Q/zKqG6lNfj1UuYcXbG4sdjpmZtVFOfgpjZ0lTyK7amiLpRWCnYgfVEh02diAbNwf3+dSXmZkViU97FcaoYgfQWkyoKGdwr87c+eJ8PrP70GKHY2ZmbZBbfgogImaT3X35w+n1Wrxua5U962sQj762hJXrfOrLzMyan7+gC0DS94FvA+emog7A9cWLqGU7fJdBbNhc5VNfZmZWFE5+CuNTwCdIj7SIiHlAj6JG1ILtWlHOsD5dufq/M4mo9dmsZmZmTcbJT2FsiOxbPAAkdStyPC1au3bizI/swNQ3V3LXVD/uwszMmpeTn8K4RdIfgHJJJwP3AX8sckwt2qd2HcL2/btz4T2vsLnKrT9mZtZ8nPwUQERcCNwG/JXsEvfzIuKi4kbVspW1E9/86I7MWLyGvz3/ZrHDMTOzNsSXuheApD7As+nvnbKIWFa8qFq+Q8cOZJchvfjNva/y8fGD6NS+rNghmZlZG+CWn8KYD0wiS35y/1s9JHH2ITvx5vK3ufmZOcUOx8zM2ggnP4UxPSJGRMR2uf+LHVRr8KEd+rLndn246IFK3t6wudjhmJlZG+DkpzB6STpS0qGSxkny6cQ8SeKcQ3Zi8ar1XPvErGKHY2ZmbYCTn8J4GPgMcCJwGTBL0mENTSTpakmLJE3NKfulpJfTM8L+Jqk8Z9i5kiolvSLpkCaoR1HsMbwPB+7Uj8semuG7PpuZWZNz8lMAEXFCRBwXEZ+LiA8ABwC/zGPSa4BDa5TdC4yNiHHAq6S7RksaDRwFjEnTXCqpZHoIf/PgnVjx9kaufOT1YodiZmYlzslPAaSrvd4REZXARxuaLiIeAZbVKLsnIjalt08C1U//PBK4KSLWR8RMoBLYc2tjbynGDunFEeMGceVjM1myen2xwzEzsxLm5KcwnpJ0q6TDJQkgIuYXYL5fAf6TXg8Bci+JmpvK3kfSKZImSZq0ePHiAoTRPP73ozuybuNmLntoRrFDMTOzEubkpzB2BK4AjgUqJf1E0o5bM0NJ3wM2ATdUF9UyWq23Ro6IKyJiYkRM7Nev39aE0axG9uvOZ3cfynVPzmbe8reLHY6ZmZUoJz8FEJl7I+Jo4CTgeOAZSQ9L2mdL5yfpeOBjwBfj3Sd/zgUqckYbCszbytBbnDM/sgMEXPTAa8UOxczMSpSTnwKQtI2ksyRNAs4GzgC2Ab4J/GUL53Uo8G3gExGxNmfQHcBRkjpJ2g7YAXi6IBVoQYb27soxew3jlklzeX3x6mKHY2ZmJcjJT2E8AfQEPhkRR0TE7RGxKSImAZfXNZGkG9O0O0maK+lE4GKgB3CvpMmSLgeIiGnALcB04C7gtIgoybsCnnbg9nRu346f/eflYodiZmYlSO+eVbHGkqRooSty4sSJMWlS63vSxiUPVvLLu1/hLyftxb7b9y12OGbWxkh6NiImFjsOaxpu+SmMByS976/YQbVmJ+63HUPKu/DDf01nc1WLzCvNzKyVcvJTGGcD3wIGA+fk/Fkjde5QxncPH8XLC1ZxyyQ/9NTMzArHz6AqgIh4FkDS29WvbesdvstA9hjemwvvfoUjxg2iZ+cOxQ7JzMxKgFt+CsvnZwpIEud9bAzL1m7gkgcrix2OmZmVCCc/BSBplaSVwDhJK3Pe21baZWgvPrPbUP702CxmL11T7HDMzKwEOPkpgIjoERE9I6J9+t8jInoWO65Scc4hO9G+TPz0Tl/6bmZmW8/Jj7V4A3p25n8OGMld0xbwxIylxQ7HzMxaOSc/1iqc9MERDCnvwo986buZmW0lJz/WKnTuUMZ3DtuZ6fNXctuzvvTdzMwaz8lPgUgaL+n09De+2PGUoo+NG8Tu2/bml3e/yqp1G4sdjpmZtVJOfgpA0lnADUD/9He9pDOKG1XpyS59H82S1eu59KEZxQ7HzMxaKSc/hXEisFdEnBcR5wF7AycXOaaSNL6inE/vNoSrHp3JM7OWFTscMzNrhZz8FIaA3Cesb05l1gTOPWwUQ/t04birnuax15YUOxwzM2tlnPwUxp+ApySdL+l84EngquKGVLr69ejEzafsw7bbdOUr1z7DfdMXFjskMzNrRZz8FEBE/Bo4AVgGvAWcEBG/LWpQJa5fj07cdMrejBrYg1Ovf5Z/TZlX7JDMzKyVcPJTODMi4vfAU8AQSX5obBMr79qR60/ai12HlXPmjc9zq5/+bmZmeXDyUwCS/gK8JOkK4CfAqcD1eUx3taRFkqbmlPWRdK+k19L/3jnDzpVUKekVSYc0RV1amx6dO3DtV/bkA9v35ZzbpnDdE7OKHZKZmbVwTn4KYyIwAvgUcFBEfAwYm8d01wCH1ij7DnB/ROwA3J/eI2k0cBQwJk1zqaSygkTfynXt2J4/HjeRg0b15//9YxpXPOLL4M3MrG5OfgpjdUSsA+ZERFUq29DQRBHxCFk/oVxHAtem19cCn8wpvyki1kfETKAS2HNrAy8VnTuUcdmXdudj4wbxkztf5tf3vEKEH4NhZmbv534phTFe0kqga/ovoHMj5zUgIuYDRMR8Sf1T+RCyq8iqzU1l7yPpFOAUgGHDhjUyjNanQ1k7fnfUrnTpUMbvH6ikcvFqfvnZ8XTr5M3czMze5ZafAoiIsojoGRHt0/8eEdGhwIup7b5BtTZtRMQVETExIib269evwGG0bGXtxC8+O47vHr4zd01dwKcu/S+zlqwpdlhmZtaCOPkpsHSfn62xUNKgNK9BwKJUPheoyBlvKODru2shiVM+NJI/f2UvFq9az8cvfowHX17U8IRmZtYmOPkpvE9s5fR3AMen18cD/8gpP0pSJ0nbATsAT2/lskrafjv05Y7T96Oid3YzxIsfeI2qKvcDMjNr65z8FF7ej7WQdCPwBLCTpLmSTgR+BnxU0mvAR9N7ImIacAswHbgLOC0iNtc+Z6tW0acrf/3avhw5fjAX3vMqp17/rJ8Ib2bWxslXxBSWpHY5V3wV3cSJE2PSpEnFDqPoIoI//XcWF9z5EsO36coVx01kZL/uxQ7LzFooSc9GxMRix2FNw5fBFICkO2q8ByAitvYUmBWIJL6y33aMGtST0//yHEdf8ST/OnM/+vdo7EV5ZmbWWjn5KYxRwEnFDsIats/Ibbjh5L345CX/5fQbnueGk/eiQ5nP/pqZtSU+6hfGqoh4uOZfsYOy2u08sCc//8w4np61jJ/e+XKxwzEzs2bm5KcwxktaLmmBpOckXSSpb7GDsrodOWEIX953OFf/dyZ3vOA7BpiZtSVOfgogIsqAPsBI4AvAAt59RIW1UN87YhR7DO/Nt2+bwisLVhU7HDMzayZOfgokIqoiYk1EvBYRF5Bdjm4tWIeydlxyzG5079yeU69/lpW+BN7MrE1w8lMgkj4h6cL09/GIuKjYMVnD+vfszKVf3I05y9byvze/4Jsgmpm1AU5+CkDST4GzyG5AOB04M5VZK7DH8D5874hR3PfSQi59qLLY4ZiZWRPzpe6FcQQwofrmhpKuBZ4Hzi1qVJa3L+87nMlzlvOre19ll6Hl7L9j23ogrJlZW+Lkp3DKgWXpda8ixmGNIImffnoXXlmwirNuep4ffGIMndrX3jDaoawdH9i+L507lDVzlGZmVghOfgrjp8Dzkh4ke7bXh4DvFjck21JdO7bn8i/tzpGX/Jezbppc77h7j+jDlcfvQfdO3oXMzFobP9urQCQNAvYgS36eiogFRQ4J8LO9GmPF2o3MW/F2ncMnz1nO//19KuOG9uKaE/akV5cOzRidmTUHP9urtPln61aQdERE/BsgIuYDd6TyHpIuiogzihqgNUqvrh3o1bXuhGbUoJ707tqRM258jmP++CTXnbgXfbp1bMYIzcxsa/hqr63zO0kn5hZIOgaYAiwqTkjWHA4dO5A/HjeRykWr+cIfnmDRynXFDsnMzPLk5GfrfBA4TdJ5knaUdB/wJeCgiPhRkWOzJnbATv255oQ9eXP523zuD08w9621xQ7JzMzy4ORnK6RTXfuTJUFTgCsj4vCImFHcyKy57DNyG64/aS+WrdnA5y9/gplL1hQ7JDMza4CTn60UEauAw4BbgGMkdS7EfCV9Q9I0SVMl3Sips6Q+ku6V9Fr637sQy7Kts9uw3tx48t6s21TF5//wBK8u9HPCzMxaMic/W0HSKkkrye7v8yngY8CynPLGzncIcCYwMSLGAmXAUcB3gPsjYgfg/vTeWoCxQ3px8yl7I+ALf3iCp15fWuyQzMysDk5+tkJE9IiInumvR0S0i4iu1eVbOfv2QBdJ7YGuwDzgSN59Wvy1wCe3chlWQDsM6MEtX92H3t068sUrn+Ka/87Et5IwM2t5nPy0QBHxJnAh8AYwH1gREfcAA1I/o+r+Rv1rm17SKZImSZq0ePHi5grbgOF9u/H30z7AATv15/x/Tuebt77Auo2bix2WmZnlcPLTAqW+PEcC2wGDgW6SvpTv9BFxRURMjIiJ/fr5GVXNrWfnDlxx7O5846Aduf25N/ns5Y/7SjAzsxbEyU/LdBAwMyIWR8RG4HZgX2BhupN09R2lfS+hFqpdO3HWQTtw1fETmb1kLZ+4+L88PmNJscMyMzOc/LRUbwB7S+oqScBHgJfI7iB9fBrneOAfRYrP8vSRUQP4x+kfoE+3jhx71dNc+ejr7gdkZlZkfrZXCyXpB8AXgE3A88BJQHeyS+qHkSVIn4uIZXXOBD/bq6VYvX4TZ9/yAndNW8DeI/owoGfdd0To2bkD2/fvzvb9uzOyX3cG9OxElgObWXPxs71Km5OfEufkp+WICC5/+HVunTSHqnr2u6VrNrBq3aZ33vfo1J4R/buzfb/ujOzfjUPHDGREv+7NEbJZm+Xkp7Q5+SlxTn5an4hg8ar1VC5aTeXi1cxI/ysXrWbhyvV0LGvH6R/enlP3H0nH9j5zbdYUnPyUNj/V3ayFkUT/np3p37Mz+27f9z3DFq5cx4/+NZ1f3/sq/5oyj59+ehy7b+sbfZuZbQn/bDRrRQb07MzFx+zG1V+eyOp1m/js5Y9z3j+msmrdxmKHZmbWajj5MWuFPrzzAO753/05fp/hXPfkbA7+zSPcN31hscMyM2sVnPyYtVLdO7Xn/E+M4fav7UuvLh046c+TOO2G51i0al2xQzMza9Gc/Ji1crsO680/z9iPcw7ZiXtfWshBv3qYm55+w/cTMjOrg5MfsxLQoawdpx24PXed9UFGD+7Jd25/kaOueJLXF68udmhmZi2Okx+zEjKiX3duPHlvfv6ZXXhp/koO/d2jXPzAa2zYVFXs0MzMWgwnP2YlRhJf2GMY931zfz46egAX3vMqH7/oMZ5/461ih2Zm1iI4+TErUf17dOaSY3bjyuMmsnLdRj592eOcf8c0lq5eX+zQzMyKyjc5NCtxB40ewN4jt+HCu1/h2idmcdMzb3D0nsM45UMjGNSrS7HDMzNrdn68RYnz4y0sV+WiVVz20Ov8ffKbtBN8ZrehnLr/SIb37Vbs0MxaFD/eorQ5+SlxTn6sNnOWreWKR17n5klz2LS5iiPGDeZ/DhjJqEE9ix2aWYvg5Ke0OfkpcU5+rD6LVq3jqkdncv2Ts1mzYTP779iPj48fzEGj+lPetWOxwzMrGic/pc3JT4lz8mP5WL52A9c8Poubn5nD/BXrKGsn9h7Rh0PHDOTgMQMZ0LNzsUM0a1ZOfkqbk58S5+THtkREMGXuCu6etoC7pi3g9cVrANh1WDmHjhnI+Ipy2kmNmnc7wc6DetK9k6+zsJbPyU9pc/LTQkkqB64ExgIBfAV4BbgZGA7MAj4fEfXevMXJj22NykWruGtqlghNfXPlVs+vY/t2fGiHvhw8ZiAHjRpAn24+tWYtk5Of0ubkp4WSdC3waERcKakj0BX4LrAsIn4m6TtA74j4dn3zcfJjhTL3rbXMXrq20dOv27iZxyqXcM+0hby5/G3K2ok9h/fh0LEDOXjMAF92by2Kk5/S5uSnBZLUE3gBGBE5H5CkV4ADImK+pEHAQxGxU33zcvJjLU1EMPXNle+cWqtclD1/bHxFOYeMGcChYwYyol/3vOa1ftNmHq9cyj3TFxABX9lvO3Yc0KMpw7c2wslPaXPy0wJJmgBcAUwHxgPPAmcBb0ZEec54b0VE71qmPwU4BWDYsGG7z549uxmiNmucykWruXvaAu6etoApc1cAsOOA7hwyZiCHjBnImME9UU4/ozXrN/HQK4u5a9oCHnx5EavXb6J7p/ZURbB2w2YOHj2A0w7cnvEV5UWqkZUCJz+lzclPCyRpIvAk8IGIeErS74CVwBn5JD+53PJjrcm85W9zT2oRenrmMqoChpR34dCxAxnRrxsPvryIR15bwoZNVfTp1pGDRw/gkDED2Xf7bVi7fjN/enwW1/x3JivXbeKDO/Tlfw7Ynr1H9HlP8mSWDyc/pc3JTwskaSDwZEQMT+8/CHwH2B6f9rI2Yunq9dz/0iLumraAx15bwobNVQwp78LB6dTYxOF9KGv3/qRm9fpN3PDkbP746EyWrF7P7tv25rQDR3LgTv2dBFnenPyUNic/LZSkR4GTIuIVSecD1c8fWJrT4blPRHyrvvk4+bFSsGrdRhauXMfIft3zTmDWbdzMrZPmcPnDr/Pm8rcZNagnpx04ksPGDqo1aTLL5eSntDn5aaFSv58rgY7A68AJQDvgFmAY8AbwuYhYVt98nPxYW7dxcxX/mDyPSx+q5PXFa9iubze+tv9IPrnrEDq2b1fndBHBS/NXcfe0BTwxYykbNlc1Oob+PTrx0dEDOGjUAHr78v5WwclPaXPyU+Kc/JhlNlcF90xbwMUPVjJt3koG9+rMKR8awVF7DqNzhzIAqqqC5+e8xV1TF3D3tIW8sWwtEowfWk7PLh0avewZi1a/c3n/Xtuly/tHD2RgL985u6Vy8lPanPyUOCc/Zu8VETz86mIuebCSZ2a9Rd/uHfnS3tuyeNV67pm+kMWr1tOhTHxg+74cOmYgB40eQN/unbZ6mVPfXMld0+Zz19QFzEh3zp5QUc4hYway44DuNLY7UjuJij5d2bZPV9qX1d2StaWWrdnAjMWrWbVuY53jSGLitr3p0bnxiWFL5eSntDn5KXFOfszq9vTMZVzyYCUPv7qYrh3LOGCnfhwyZiAH7tyfnk34hV65aBV3T1v4nsv7t1aHMjF8m25s37872/fvzsh+2f+K3l0pK6s7s3orJTmVi1a/879y0WreWlt30pNrQM9O/PDIsRwyZmBB6pGvqqpAosk6sTv5KW1Ofkqckx+zhr25/G226dbxndNfzWn+irdZtHJ9o6ffuLmKWUvXvpO0zFi8mtlL11DViEN7764d3pM4jezfnT5d6+6jtGztBn7+n5d5ecEqDh0zkB8cOaZZHoJbuWgVX73uWTZVBafuP5JP7zaETu0L+9k5+SltTn5KnJMfs7Zn/abNzE4J0bzlb1PfYb5bp/aM7Je1GG3TiNN7GzdXccUjr/O7+1+jU/t2nHvYKI7ao4J2TXRF3d3TFvC/N0+mS8cyBpd3YcrcFQzs2ZmTPzSCo/esoGvHwjw418lPaXPyU+Kc/JhZc5i5ZA3fvf1Fnnh9KXsO78NPPr0L2/fP7zEl+dhcFfz2vle56IFKxg/txeXH7s7Anp15rHIJlzxYyZOvL6NPt4585QPDOXaf4fTaig7q4OSn1Dn5KXFOfsysuUQEt06aywV3vsTbGzZz6gEjGT2o7metde3Ynj2369Pg6cYVb2/k6zc9z4OvLObzE4fywyPHvm+aZ2cv45IHZ/DAy4vo0ak9x+6zLV/Zb7tGd1Z38lPanPyUOCc/ZtbcFq9azw/+OY1/TZnf4LhdOry3o3nNFptXFqziq9dN4s3lb/P9j4/hi3sNq7eT87R5K7j0oRnc+eJ8TtpvO753xOhG1cHJT2lz8lPinPyYWbHMXrqGtRs21zl80ar13Dt9AfdMW8iidIuBfUf25ZAxA/no6AE8M2sZZ9/6At06teeyL+7GxOF98l72jMWr6dm5A/16uOXH3s/JT4lz8mNmLV12c8nl3D1tAXdNXfDOzSUjYLdh5Vz2pd2b5SqyXE5+SpuTnxLn5MfMWpOI4OUF2WNF2rcTJ39oRMEvY8+Hk5/SVphrAs3MzApAEqMG9WTUoJ7FDsVKWOHuhW5mZmbWCjj5MTMzszbFyY+ZmZm1KU5+zMzMrE1x8mNmZmZtipMfMzMza1Oc/JiZmVmb4uTHzMzM2hTf4bnESVoMzG7k5H2BJQUMpzVwndsG17lt2Jo6bxsR/QoZjLUcTn6sTpImtbXbu7vObYPr3Da0xTpbfnzay8zMzNoUJz9mZmbWpjj5sfpcUewAisB1bhtc57ahLdbZ8uA+P2ZmZtamuOXHzMzM2hQnP2ZmZtamOPkxJB0q6RVJlZK+U8twSfp9Gj5F0m7FiLOQ8qjzF1Ndp0h6XNL4YsRZSA3VOWe8PSRtlvTZ5oyvKeRTZ0kHSJosaZqkh5s7xkLKY7vuJemfkl5I9T2hGHEWkqSrJS2SNLWO4SV3/LICiAj/teE/oAyYAYwAOgIvAKNrjHM48B9AwN7AU8WOuxnqvC/QO70+rC3UOWe8B4A7gc8WO+5m+JzLgenAsPS+f7HjbuL6fhf4eXrdD1gGdCx27FtZ7w8BuwFT6xheUscv/xXmzy0/tidQGRGvR8QG4CbgyBrjHAn8OTJPAuWSBjV3oAXUYJ0j4vGIeCu9fRIY2swxFlo+nzPAGcBfgUXNGVwTyafOxwC3R8QbABHRmuudT30D6CFJQHey5GdT84ZZWBHxCFk96lJqxy8rACc/NgSYk/N+birb0nFaky2tz4lkvxxbswbrLGkI8Cng8maMqynl8znvCPSW9JCkZyUd12zRFV4+9b0YGAXMA14EzoqIquYJr2hK7fhlBdC+2AFY0amWspr3P8hnnNYk7/pIOpAs+dmvSSNqevnU+bfAtyNic9Yw0OrlU+f2wO7AR4AuwBOSnoyIV5s6uCaQT30PASYDHwZGAvdKejQiVjZxbMVUascvKwAnPzYXqMh5P5TsV+GWjtOa5FUfSeOAK4HDImJpM8XWVPKp80TgppT49AUOl7QpIv7eLBEWXr7b9pKIWAOskfQIMB5ojclPPvU9AfhZRARQKWkmsDPwdPOEWBSldvyyAvBpL3sG2EHSdpI6AkcBd9QY5w7guHTVxN7AioiY39yBFlCDdZY0DLgdOLaVtgLU1GCdI2K7iBgeEcOB24D/acWJD+S3bf8D+KCk9pK6AnsBLzVznIWST33fIGvlQtIAYCfg9WaNsvmV2vHLCsAtP21cRGySdDpwN9nVIldHxDRJp6bhl5Nd+XM4UAmsJfv12GrlWefzgG2AS1NLyKZoxU+HzrPOJSWfOkfES5LuAqYAVcCVEVHrJdMtXZ6f8Y+AayS9SHY66NsRsaRoQReApBuBA4C+kuYC3wc6QGkev6ww/HgLMzMza1N82svMzMzaFCc/ZmZm1qY4+TEzM7M2xcmPmZmZtSlOfszMzKxNcfJjVkTp6emTJU2VdGu610zJkvRlSRc3MM4sSX2bK6bmIum49DlPkzRd0tnFjsmsrXLyY1Zcb0fEhIgYC2wATi12QFZ4kg4Dvg4cHBFjyJ5CvqKoQZm1YU5+zFqOR4HtAST9PT1oc5qkU6pHkPSEpOdT+WdS2TWS5koqS++/JikkDU/vvyTp6dTC9Iec8VZL+pWk5yTdL6lfzYDSvD+bXl8m6fz0ets0zZT0f1gqfzTN77+S9ktlHSTdIul5sgenjpX0ZBqnXxrnIEmvSroN6Aj8StJLkk5Lww+Q9K/0uo+kFdUtJ+mhpBNzYl6d8/qdViRJ10uaml6XSfqlpGdSHb5acznp/dmSzpf0wbT+pkt6O72enMY5L81nqqQrpFofjHYucHZEzAOIiHUR8cf6NwczaypOfsxaAEntgcPInrQN8JWI2J3seVtnStoGICL2iYhdgW8AuadN3iR7aCXAkWR3s0XSKOALwAciYgKwGfhiGq8b8FxE7AY8THZn3LriOw8oi4jzU9HFwJ8jYhxwA/D7VH5Qmt+ngIskdU/LX5finkH2UMl9gZuB76TpLgGOAM4CugPXprp/vZak7Fxgdl2x1hH/LsDYnKITyR5zsAewB3CypO3qmj4iHk3r73BgRmqtm1C9LiJij9R61wX4WC2zGAs8uyUxm1nT8eMtzIqrS3ULAlnLz1Xp9ZmSPpVeVwA7AEsl9QceBIYBR+fM5zrgWElvAK+RPbwRsuc47Q48kxokugCL0rAqsgQE4HqyZ5nV5svAR3nvwyH3AT6ds+xfpNcfl/R/6fVwYFey5OK+VDYF6BgRVZLuB/4gqTfQISJeA5C0DJgSEWvSuhkPbErDhgB7A3+rI9a6/JgsubsgvT8YGFfdqgX0IlvHG8ie9TU5lfcDGmqhOVDSt4CuQB9gGvDPLYzPzJqRkx+z4no7pwUByE69AAcB+0TEWkkPAZ0BImIRMEbSPsD/AdWnaBaQPc/oHOB3wIHVswOujYhz84ilrmfd9CFraboQOK6+aSPiNrKHopLijhRDXdTAcGoM/z7Z86n2bWCaXPsCq4EXaszzjIi4+z0Lytb9oxHxsfT+bLKWqNoDkzoDlwITI2JOOi3YuZZRp5EloQ9sQdxm1kR82sus5ekFvJUSn53JWjqQ1FlSpzTOOt57GgfgT0D/iHgup+x+4LOpxai6v8y2aVg7oLrl4xjgsTri+XVEXAoMlnRwKnuc7KnhkJ1GeyzNf1D6PxHYEZgMTCJL5gDGkSVv7chapZ6JiGXAZknbp5adPmStMt3IWo6mpGlHAsMj4p464qzL+WQPqs11N/A1SR1SvDum5W2p6kRnSTrF99k6xvsp8AtJA9PyOkk6sxHLM7MCcMuPWctzF3CqpCnAK8CTqXwA8I/UobY92dVD74iIfwP/rlE2PZ2GuiclHBuB08j6zKwhS0SeJbvy6AsNxPVV4A5JewBnAldLOgdYzLtPyr49JRGbgaMjYrWkm4BPplNJs9J4j5O1ClWf2jsD+A9ZsrSarIXpUuCiiFiY+i7tTN1P5L4yp6NzF0kXRcQZ6f1TETFDqQN49fhkp+WeS+tzMfDJBur/PhGxXNIfyfpqzQKeqWO8OyUNAO5Lywvg6i1dnpkVhp/qbtZGSVodEXWe0mmiZX6Z7BTR6fWMMyuNs2QrlvNQRBzQ2OnNrLT5tJeZlaKrGh7FzNoqt/yYmZlZm+KWHzMzM2tTnPyYmZlZm+Lkx8zMzNoUJz9mZmbWpjj5MTMzszbl/wMezWVQPsqVkgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1_zero_stat = (df_l1 == 0).sum()\n",
    "plt.plot(c_values, l1_zero_stat)\n",
    "plt.title('Зависимость количества нулевых весов от степени размера параметра регуляризации')\n",
    "plt.xlabel('Размер коэффициента С')\n",
    "plt.ylabel('Кол-во нулевых весов')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Как видно из полученного графика чем меньше значение С, тем больше сила регуляризации и большее количество признаков обнуляются через нулевые веса.\n",
    "\n",
    "Теперь посмотрим как изменяются размеры весов в зависимости от размера коэфициента регуляризации."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Таблица статистических показателей для признаков с L1-регуляризацией\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>playoffs</th>\n",
       "      <th>shot_distance</th>\n",
       "      <th>last_5_sec_in_period</th>\n",
       "      <th>home_play</th>\n",
       "      <th>action_type_Alley Oop Dunk Shot</th>\n",
       "      <th>action_type_Alley Oop Layup shot</th>\n",
       "      <th>action_type_Driving Dunk Shot</th>\n",
       "      <th>action_type_Driving Finger Roll Layup Shot</th>\n",
       "      <th>action_type_Driving Finger Roll Shot</th>\n",
       "      <th>action_type_Driving Jump shot</th>\n",
       "      <th>action_type_Driving Layup Shot</th>\n",
       "      <th>action_type_Driving Reverse Layup Shot</th>\n",
       "      <th>action_type_Driving Slam Dunk Shot</th>\n",
       "      <th>action_type_Dunk Shot</th>\n",
       "      <th>action_type_Fadeaway Bank shot</th>\n",
       "      <th>action_type_Fadeaway Jump Shot</th>\n",
       "      <th>action_type_Finger Roll Layup Shot</th>\n",
       "      <th>action_type_Finger Roll Shot</th>\n",
       "      <th>action_type_Floating Jump shot</th>\n",
       "      <th>action_type_Follow Up Dunk Shot</th>\n",
       "      <th>action_type_Hook Shot</th>\n",
       "      <th>action_type_Jump Bank Shot</th>\n",
       "      <th>action_type_Jump Hook Shot</th>\n",
       "      <th>action_type_Jump Shot</th>\n",
       "      <th>action_type_Layup Shot</th>\n",
       "      <th>action_type_Other</th>\n",
       "      <th>action_type_Pullup Jump shot</th>\n",
       "      <th>action_type_Putback Layup Shot</th>\n",
       "      <th>action_type_Reverse Dunk Shot</th>\n",
       "      <th>action_type_Reverse Layup Shot</th>\n",
       "      <th>action_type_Reverse Slam Dunk Shot</th>\n",
       "      <th>action_type_Running Bank shot</th>\n",
       "      <th>action_type_Running Dunk Shot</th>\n",
       "      <th>action_type_Running Hook Shot</th>\n",
       "      <th>action_type_Running Jump Shot</th>\n",
       "      <th>action_type_Running Layup Shot</th>\n",
       "      <th>action_type_Slam Dunk Shot</th>\n",
       "      <th>action_type_Step Back Jump shot</th>\n",
       "      <th>action_type_Tip Shot</th>\n",
       "      <th>action_type_Turnaround Bank shot</th>\n",
       "      <th>action_type_Turnaround Fadeaway shot</th>\n",
       "      <th>action_type_Turnaround Jump Shot</th>\n",
       "      <th>combined_shot_type_Bank Shot</th>\n",
       "      <th>combined_shot_type_Dunk</th>\n",
       "      <th>combined_shot_type_Hook Shot</th>\n",
       "      <th>combined_shot_type_Jump Shot</th>\n",
       "      <th>combined_shot_type_Layup</th>\n",
       "      <th>combined_shot_type_Tip Shot</th>\n",
       "      <th>period_1</th>\n",
       "      <th>period_2</th>\n",
       "      <th>period_3</th>\n",
       "      <th>period_4</th>\n",
       "      <th>period_5</th>\n",
       "      <th>period_6</th>\n",
       "      <th>period_7</th>\n",
       "      <th>season_1996-97</th>\n",
       "      <th>season_1997-98</th>\n",
       "      <th>season_1998-99</th>\n",
       "      <th>season_1999-00</th>\n",
       "      <th>season_2000-01</th>\n",
       "      <th>season_2001-02</th>\n",
       "      <th>season_2002-03</th>\n",
       "      <th>season_2003-04</th>\n",
       "      <th>season_2004-05</th>\n",
       "      <th>season_2005-06</th>\n",
       "      <th>season_2006-07</th>\n",
       "      <th>season_2007-08</th>\n",
       "      <th>season_2008-09</th>\n",
       "      <th>season_2009-10</th>\n",
       "      <th>season_2010-11</th>\n",
       "      <th>season_2011-12</th>\n",
       "      <th>season_2012-13</th>\n",
       "      <th>season_2013-14</th>\n",
       "      <th>season_2014-15</th>\n",
       "      <th>season_2015-16</th>\n",
       "      <th>shot_type_2PT Field Goal</th>\n",
       "      <th>shot_type_3PT Field Goal</th>\n",
       "      <th>shot_zone_area_Back Court(BC)</th>\n",
       "      <th>shot_zone_area_Center(C)</th>\n",
       "      <th>shot_zone_area_Left Side Center(LC)</th>\n",
       "      <th>shot_zone_area_Left Side(L)</th>\n",
       "      <th>shot_zone_area_Right Side Center(RC)</th>\n",
       "      <th>shot_zone_area_Right Side(R)</th>\n",
       "      <th>shot_zone_basic_Above the Break 3</th>\n",
       "      <th>shot_zone_basic_Backcourt</th>\n",
       "      <th>shot_zone_basic_In The Paint (Non-RA)</th>\n",
       "      <th>shot_zone_basic_Left Corner 3</th>\n",
       "      <th>shot_zone_basic_Mid-Range</th>\n",
       "      <th>shot_zone_basic_Restricted Area</th>\n",
       "      <th>shot_zone_basic_Right Corner 3</th>\n",
       "      <th>shot_zone_range_16-24 ft.</th>\n",
       "      <th>shot_zone_range_24+ ft.</th>\n",
       "      <th>shot_zone_range_8-16 ft.</th>\n",
       "      <th>shot_zone_range_Back Court Shot</th>\n",
       "      <th>shot_zone_range_Less Than 8 ft.</th>\n",
       "      <th>game_year_1996</th>\n",
       "      <th>game_year_1997</th>\n",
       "      <th>game_year_1998</th>\n",
       "      <th>game_year_1999</th>\n",
       "      <th>game_year_2000</th>\n",
       "      <th>game_year_2001</th>\n",
       "      <th>game_year_2002</th>\n",
       "      <th>game_year_2003</th>\n",
       "      <th>game_year_2004</th>\n",
       "      <th>game_year_2005</th>\n",
       "      <th>game_year_2006</th>\n",
       "      <th>game_year_2007</th>\n",
       "      <th>game_year_2008</th>\n",
       "      <th>game_year_2009</th>\n",
       "      <th>game_year_2010</th>\n",
       "      <th>game_year_2011</th>\n",
       "      <th>game_year_2012</th>\n",
       "      <th>game_year_2013</th>\n",
       "      <th>game_year_2014</th>\n",
       "      <th>game_year_2015</th>\n",
       "      <th>game_year_2016</th>\n",
       "      <th>game_month_1</th>\n",
       "      <th>game_month_2</th>\n",
       "      <th>game_month_3</th>\n",
       "      <th>game_month_4</th>\n",
       "      <th>game_month_5</th>\n",
       "      <th>game_month_6</th>\n",
       "      <th>game_month_10</th>\n",
       "      <th>game_month_11</th>\n",
       "      <th>game_month_12</th>\n",
       "      <th>opponent_ATL</th>\n",
       "      <th>opponent_BKN</th>\n",
       "      <th>opponent_BOS</th>\n",
       "      <th>opponent_CHA</th>\n",
       "      <th>opponent_CHI</th>\n",
       "      <th>opponent_CLE</th>\n",
       "      <th>opponent_DAL</th>\n",
       "      <th>opponent_DEN</th>\n",
       "      <th>opponent_DET</th>\n",
       "      <th>opponent_GSW</th>\n",
       "      <th>opponent_HOU</th>\n",
       "      <th>opponent_IND</th>\n",
       "      <th>opponent_LAC</th>\n",
       "      <th>opponent_MEM</th>\n",
       "      <th>opponent_MIA</th>\n",
       "      <th>opponent_MIL</th>\n",
       "      <th>opponent_MIN</th>\n",
       "      <th>opponent_NJN</th>\n",
       "      <th>opponent_NOH</th>\n",
       "      <th>opponent_NOP</th>\n",
       "      <th>opponent_NYK</th>\n",
       "      <th>opponent_OKC</th>\n",
       "      <th>opponent_ORL</th>\n",
       "      <th>opponent_PHI</th>\n",
       "      <th>opponent_PHX</th>\n",
       "      <th>opponent_POR</th>\n",
       "      <th>opponent_SAC</th>\n",
       "      <th>opponent_SAS</th>\n",
       "      <th>opponent_SEA</th>\n",
       "      <th>opponent_TOR</th>\n",
       "      <th>opponent_UTA</th>\n",
       "      <th>opponent_VAN</th>\n",
       "      <th>opponent_WAS</th>\n",
       "      <th>loc_x_(-250.498, -230.08]</th>\n",
       "      <th>loc_x_(-230.08, -210.16]</th>\n",
       "      <th>loc_x_(-210.16, -190.24]</th>\n",
       "      <th>loc_x_(-190.24, -170.32]</th>\n",
       "      <th>loc_x_(-170.32, -150.4]</th>\n",
       "      <th>loc_x_(-150.4, -130.48]</th>\n",
       "      <th>loc_x_(-130.48, -110.56]</th>\n",
       "      <th>loc_x_(-110.56, -90.64]</th>\n",
       "      <th>loc_x_(-90.64, -70.72]</th>\n",
       "      <th>loc_x_(-70.72, -50.8]</th>\n",
       "      <th>loc_x_(-50.8, -30.88]</th>\n",
       "      <th>loc_x_(-30.88, -10.96]</th>\n",
       "      <th>loc_x_(-10.96, 8.96]</th>\n",
       "      <th>loc_x_(8.96, 28.88]</th>\n",
       "      <th>loc_x_(28.88, 48.8]</th>\n",
       "      <th>loc_x_(48.8, 68.72]</th>\n",
       "      <th>loc_x_(68.72, 88.64]</th>\n",
       "      <th>loc_x_(88.64, 108.56]</th>\n",
       "      <th>loc_x_(108.56, 128.48]</th>\n",
       "      <th>loc_x_(128.48, 148.4]</th>\n",
       "      <th>loc_x_(148.4, 168.32]</th>\n",
       "      <th>loc_x_(168.32, 188.24]</th>\n",
       "      <th>loc_x_(188.24, 208.16]</th>\n",
       "      <th>loc_x_(208.16, 228.08]</th>\n",
       "      <th>loc_x_(228.08, 248.0]</th>\n",
       "      <th>loc_y_(-44.835, -10.6]</th>\n",
       "      <th>loc_y_(-10.6, 22.8]</th>\n",
       "      <th>loc_y_(22.8, 56.2]</th>\n",
       "      <th>loc_y_(56.2, 89.6]</th>\n",
       "      <th>loc_y_(89.6, 123.0]</th>\n",
       "      <th>loc_y_(123.0, 156.4]</th>\n",
       "      <th>loc_y_(156.4, 189.8]</th>\n",
       "      <th>loc_y_(189.8, 223.2]</th>\n",
       "      <th>loc_y_(223.2, 256.6]</th>\n",
       "      <th>loc_y_(256.6, 290.0]</th>\n",
       "      <th>loc_y_(290.0, 323.4]</th>\n",
       "      <th>loc_y_(323.4, 356.8]</th>\n",
       "      <th>loc_y_(356.8, 390.2]</th>\n",
       "      <th>loc_y_(390.2, 423.6]</th>\n",
       "      <th>loc_y_(423.6, 457.0]</th>\n",
       "      <th>loc_y_(457.0, 490.4]</th>\n",
       "      <th>loc_y_(490.4, 523.8]</th>\n",
       "      <th>loc_y_(523.8, 557.2]</th>\n",
       "      <th>loc_y_(557.2, 590.6]</th>\n",
       "      <th>loc_y_(590.6, 624.0]</th>\n",
       "      <th>loc_y_(624.0, 657.4]</th>\n",
       "      <th>loc_y_(657.4, 690.8]</th>\n",
       "      <th>loc_y_(690.8, 724.2]</th>\n",
       "      <th>loc_y_(724.2, 757.6]</th>\n",
       "      <th>loc_y_(757.6, 791.0]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.067308</td>\n",
       "      <td>0.003238</td>\n",
       "      <td>-0.719099</td>\n",
       "      <td>0.045846</td>\n",
       "      <td>0.005154</td>\n",
       "      <td>-0.007500</td>\n",
       "      <td>0.650134</td>\n",
       "      <td>0.631561</td>\n",
       "      <td>0.460566</td>\n",
       "      <td>-0.535076</td>\n",
       "      <td>0.082582</td>\n",
       "      <td>0.092887</td>\n",
       "      <td>0.146879</td>\n",
       "      <td>-1.237399</td>\n",
       "      <td>0.669684</td>\n",
       "      <td>-0.510890</td>\n",
       "      <td>0.162201</td>\n",
       "      <td>-0.629970</td>\n",
       "      <td>0.066927</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.058261</td>\n",
       "      <td>0.420556</td>\n",
       "      <td>0.001568</td>\n",
       "      <td>-1.653246</td>\n",
       "      <td>-1.398728</td>\n",
       "      <td>-0.289802</td>\n",
       "      <td>0.113922</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.377835</td>\n",
       "      <td>0.013553</td>\n",
       "      <td>0.084479</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.623469</td>\n",
       "      <td>0.224786</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.882215</td>\n",
       "      <td>-0.181078</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.357021</td>\n",
       "      <td>-0.447970</td>\n",
       "      <td>0.485737</td>\n",
       "      <td>1.629238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.010910</td>\n",
       "      <td>-1.428047</td>\n",
       "      <td>0.131309</td>\n",
       "      <td>0.078813</td>\n",
       "      <td>0.063650</td>\n",
       "      <td>-0.063605</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.006509</td>\n",
       "      <td>-0.088745</td>\n",
       "      <td>0.064861</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.067250</td>\n",
       "      <td>0.094410</td>\n",
       "      <td>0.069968</td>\n",
       "      <td>-0.002168</td>\n",
       "      <td>-0.058171</td>\n",
       "      <td>-0.015736</td>\n",
       "      <td>0.026751</td>\n",
       "      <td>0.017283</td>\n",
       "      <td>0.037092</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>-0.001977</td>\n",
       "      <td>-0.052236</td>\n",
       "      <td>0.008240</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.214846</td>\n",
       "      <td>-0.417950</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.071969</td>\n",
       "      <td>-0.625135</td>\n",
       "      <td>0.111434</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.005075</td>\n",
       "      <td>0.153678</td>\n",
       "      <td>0.133665</td>\n",
       "      <td>-0.159368</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.071976</td>\n",
       "      <td>0.251864</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.217221</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.202678</td>\n",
       "      <td>0.161808</td>\n",
       "      <td>0.163149</td>\n",
       "      <td>-0.808262</td>\n",
       "      <td>-0.004243</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.078732</td>\n",
       "      <td>0.135902</td>\n",
       "      <td>0.005563</td>\n",
       "      <td>-0.066045</td>\n",
       "      <td>-0.024721</td>\n",
       "      <td>-0.012824</td>\n",
       "      <td>0.153404</td>\n",
       "      <td>0.201618</td>\n",
       "      <td>0.059015</td>\n",
       "      <td>0.054311</td>\n",
       "      <td>0.048892</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.097646</td>\n",
       "      <td>-0.037951</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.086182</td>\n",
       "      <td>0.058367</td>\n",
       "      <td>0.030351</td>\n",
       "      <td>-0.036139</td>\n",
       "      <td>-0.025724</td>\n",
       "      <td>0.123732</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.000180</td>\n",
       "      <td>0.000503</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.020792</td>\n",
       "      <td>-0.197255</td>\n",
       "      <td>-0.047986</td>\n",
       "      <td>0.004730</td>\n",
       "      <td>0.008608</td>\n",
       "      <td>-0.017499</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001548</td>\n",
       "      <td>0.021688</td>\n",
       "      <td>-0.064887</td>\n",
       "      <td>-0.118666</td>\n",
       "      <td>-0.072942</td>\n",
       "      <td>-0.005428</td>\n",
       "      <td>-0.028353</td>\n",
       "      <td>-0.052038</td>\n",
       "      <td>0.013917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.149935</td>\n",
       "      <td>0.057026</td>\n",
       "      <td>0.002827</td>\n",
       "      <td>0.175643</td>\n",
       "      <td>-0.156082</td>\n",
       "      <td>-0.042050</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>0.100322</td>\n",
       "      <td>0.013260</td>\n",
       "      <td>0.105569</td>\n",
       "      <td>-0.008531</td>\n",
       "      <td>0.041832</td>\n",
       "      <td>-0.105710</td>\n",
       "      <td>0.010890</td>\n",
       "      <td>0.067532</td>\n",
       "      <td>0.011230</td>\n",
       "      <td>-0.005857</td>\n",
       "      <td>0.079179</td>\n",
       "      <td>0.071095</td>\n",
       "      <td>0.045831</td>\n",
       "      <td>0.070516</td>\n",
       "      <td>0.023871</td>\n",
       "      <td>-0.113778</td>\n",
       "      <td>-0.029249</td>\n",
       "      <td>0.012963</td>\n",
       "      <td>-0.066040</td>\n",
       "      <td>-0.076743</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.069959</td>\n",
       "      <td>0.048349</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.016064</td>\n",
       "      <td>-0.029035</td>\n",
       "      <td>-0.128454</td>\n",
       "      <td>-0.033072</td>\n",
       "      <td>-0.122116</td>\n",
       "      <td>-0.064741</td>\n",
       "      <td>0.060070</td>\n",
       "      <td>0.051499</td>\n",
       "      <td>-0.058648</td>\n",
       "      <td>0.093486</td>\n",
       "      <td>-0.006629</td>\n",
       "      <td>0.025924</td>\n",
       "      <td>-0.069691</td>\n",
       "      <td>0.005118</td>\n",
       "      <td>0.087115</td>\n",
       "      <td>0.319396</td>\n",
       "      <td>0.289124</td>\n",
       "      <td>0.221091</td>\n",
       "      <td>0.188956</td>\n",
       "      <td>0.043087</td>\n",
       "      <td>-0.321683</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.828901</td>\n",
       "      <td>-0.213861</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.024175</td>\n",
       "      <td>0.005957</td>\n",
       "      <td>0.119921</td>\n",
       "      <td>0.007599</td>\n",
       "      <td>0.016544</td>\n",
       "      <td>0.018458</td>\n",
       "      <td>0.310007</td>\n",
       "      <td>0.289486</td>\n",
       "      <td>0.217789</td>\n",
       "      <td>0.330806</td>\n",
       "      <td>0.060448</td>\n",
       "      <td>0.073139</td>\n",
       "      <td>0.186366</td>\n",
       "      <td>0.322674</td>\n",
       "      <td>0.383868</td>\n",
       "      <td>0.138098</td>\n",
       "      <td>0.146379</td>\n",
       "      <td>0.346350</td>\n",
       "      <td>0.050696</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.352595</td>\n",
       "      <td>0.095808</td>\n",
       "      <td>0.005273</td>\n",
       "      <td>0.287245</td>\n",
       "      <td>0.245723</td>\n",
       "      <td>0.158510</td>\n",
       "      <td>0.042905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.130736</td>\n",
       "      <td>0.042080</td>\n",
       "      <td>0.081770</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.343150</td>\n",
       "      <td>0.059780</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.351699</td>\n",
       "      <td>0.117541</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.128954</td>\n",
       "      <td>0.136443</td>\n",
       "      <td>0.163263</td>\n",
       "      <td>0.273754</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022953</td>\n",
       "      <td>0.350530</td>\n",
       "      <td>0.043514</td>\n",
       "      <td>0.040139</td>\n",
       "      <td>0.036309</td>\n",
       "      <td>0.030661</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005399</td>\n",
       "      <td>0.025019</td>\n",
       "      <td>0.022308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022799</td>\n",
       "      <td>0.052169</td>\n",
       "      <td>0.043379</td>\n",
       "      <td>0.004231</td>\n",
       "      <td>0.031107</td>\n",
       "      <td>0.023448</td>\n",
       "      <td>0.013815</td>\n",
       "      <td>0.011950</td>\n",
       "      <td>0.011251</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.001919</td>\n",
       "      <td>0.013374</td>\n",
       "      <td>0.009051</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.053138</td>\n",
       "      <td>0.073279</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.054553</td>\n",
       "      <td>0.587678</td>\n",
       "      <td>0.031290</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005270</td>\n",
       "      <td>0.069472</td>\n",
       "      <td>0.069466</td>\n",
       "      <td>0.064823</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033934</td>\n",
       "      <td>0.092533</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.077590</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050515</td>\n",
       "      <td>0.082146</td>\n",
       "      <td>0.055753</td>\n",
       "      <td>0.667419</td>\n",
       "      <td>0.020314</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.024611</td>\n",
       "      <td>0.031724</td>\n",
       "      <td>0.007400</td>\n",
       "      <td>0.039377</td>\n",
       "      <td>0.022053</td>\n",
       "      <td>0.010620</td>\n",
       "      <td>0.057814</td>\n",
       "      <td>0.053122</td>\n",
       "      <td>0.029089</td>\n",
       "      <td>0.023657</td>\n",
       "      <td>0.022011</td>\n",
       "      <td>0.001637</td>\n",
       "      <td>0.001003</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.029843</td>\n",
       "      <td>0.020758</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.036097</td>\n",
       "      <td>0.014137</td>\n",
       "      <td>0.008347</td>\n",
       "      <td>0.011831</td>\n",
       "      <td>0.007968</td>\n",
       "      <td>0.034914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000585</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.014779</td>\n",
       "      <td>0.145011</td>\n",
       "      <td>0.019083</td>\n",
       "      <td>0.004969</td>\n",
       "      <td>0.007772</td>\n",
       "      <td>0.013026</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000963</td>\n",
       "      <td>0.013169</td>\n",
       "      <td>0.025589</td>\n",
       "      <td>0.033027</td>\n",
       "      <td>0.030205</td>\n",
       "      <td>0.005180</td>\n",
       "      <td>0.015092</td>\n",
       "      <td>0.027606</td>\n",
       "      <td>0.011182</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.055223</td>\n",
       "      <td>0.026306</td>\n",
       "      <td>0.004509</td>\n",
       "      <td>0.047163</td>\n",
       "      <td>0.046583</td>\n",
       "      <td>0.020269</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>0.022442</td>\n",
       "      <td>0.005883</td>\n",
       "      <td>0.027341</td>\n",
       "      <td>0.005861</td>\n",
       "      <td>0.014831</td>\n",
       "      <td>0.041276</td>\n",
       "      <td>0.005238</td>\n",
       "      <td>0.041408</td>\n",
       "      <td>0.009353</td>\n",
       "      <td>0.010591</td>\n",
       "      <td>0.052004</td>\n",
       "      <td>0.052072</td>\n",
       "      <td>0.040132</td>\n",
       "      <td>0.045664</td>\n",
       "      <td>0.026142</td>\n",
       "      <td>0.033965</td>\n",
       "      <td>0.021985</td>\n",
       "      <td>0.016887</td>\n",
       "      <td>0.025297</td>\n",
       "      <td>0.028952</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.011627</td>\n",
       "      <td>0.019603</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.009309</td>\n",
       "      <td>0.030483</td>\n",
       "      <td>0.055897</td>\n",
       "      <td>0.034668</td>\n",
       "      <td>0.053097</td>\n",
       "      <td>0.041378</td>\n",
       "      <td>0.027891</td>\n",
       "      <td>0.027487</td>\n",
       "      <td>0.047624</td>\n",
       "      <td>0.041751</td>\n",
       "      <td>0.007918</td>\n",
       "      <td>0.017052</td>\n",
       "      <td>0.016645</td>\n",
       "      <td>0.009212</td>\n",
       "      <td>0.032611</td>\n",
       "      <td>0.065882</td>\n",
       "      <td>0.065527</td>\n",
       "      <td>0.068413</td>\n",
       "      <td>0.075383</td>\n",
       "      <td>0.034134</td>\n",
       "      <td>0.223204</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.639990</td>\n",
       "      <td>0.266243</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.083360</td>\n",
       "      <td>-0.024615</td>\n",
       "      <td>-0.752796</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.077141</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.906305</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.384945</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.634440</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.986358</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.319788</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.806051</td>\n",
       "      <td>-1.517654</td>\n",
       "      <td>-0.457941</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.492492</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.337377</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.485843</td>\n",
       "      <td>-0.573056</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.638497</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.125557</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.102067</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.013460</td>\n",
       "      <td>-0.096206</td>\n",
       "      <td>-0.055219</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.005985</td>\n",
       "      <td>-0.058976</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.241164</td>\n",
       "      <td>-0.451475</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.931117</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.015173</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.212588</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-2.109865</td>\n",
       "      <td>-0.119578</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.107593</td>\n",
       "      <td>-0.052853</td>\n",
       "      <td>-0.039895</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003285</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.121747</td>\n",
       "      <td>-0.057326</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.116345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.042875</td>\n",
       "      <td>-0.030287</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.002444</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.038113</td>\n",
       "      <td>-0.376066</td>\n",
       "      <td>-0.062038</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.033496</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.084372</td>\n",
       "      <td>-0.137458</td>\n",
       "      <td>-0.097020</td>\n",
       "      <td>-0.013179</td>\n",
       "      <td>-0.041758</td>\n",
       "      <td>-0.078049</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.190368</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.186536</td>\n",
       "      <td>-0.059513</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.015356</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.135916</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.033690</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.146263</td>\n",
       "      <td>-0.056858</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.084593</td>\n",
       "      <td>-0.096894</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.079199</td>\n",
       "      <td>-0.199490</td>\n",
       "      <td>-0.090931</td>\n",
       "      <td>-0.193177</td>\n",
       "      <td>-0.128484</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.134694</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.022062</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.087962</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.592999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.744994</td>\n",
       "      <td>-0.749138</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.081405</td>\n",
       "      <td>0.001468</td>\n",
       "      <td>-0.746102</td>\n",
       "      <td>0.047256</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.522413</td>\n",
       "      <td>0.530500</td>\n",
       "      <td>0.379979</td>\n",
       "      <td>-0.801146</td>\n",
       "      <td>0.044796</td>\n",
       "      <td>0.006824</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.363549</td>\n",
       "      <td>0.460835</td>\n",
       "      <td>-0.582212</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.891044</td>\n",
       "      <td>0.003367</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.243990</td>\n",
       "      <td>0.407514</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.749114</td>\n",
       "      <td>-1.480952</td>\n",
       "      <td>-0.400540</td>\n",
       "      <td>0.080419</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.441411</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.462241</td>\n",
       "      <td>0.182808</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.774243</td>\n",
       "      <td>-0.261163</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.426768</td>\n",
       "      <td>-0.517805</td>\n",
       "      <td>0.504212</td>\n",
       "      <td>1.628425</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.577479</td>\n",
       "      <td>0.114757</td>\n",
       "      <td>0.061710</td>\n",
       "      <td>0.045569</td>\n",
       "      <td>-0.082135</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.099508</td>\n",
       "      <td>0.068965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.058583</td>\n",
       "      <td>0.061840</td>\n",
       "      <td>0.035543</td>\n",
       "      <td>-0.001128</td>\n",
       "      <td>-0.083879</td>\n",
       "      <td>-0.037408</td>\n",
       "      <td>0.014480</td>\n",
       "      <td>0.005364</td>\n",
       "      <td>0.031289</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003286</td>\n",
       "      <td>-0.057267</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.233924</td>\n",
       "      <td>-0.438684</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.016420</td>\n",
       "      <td>0.093909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.009619</td>\n",
       "      <td>0.096234</td>\n",
       "      <td>0.083877</td>\n",
       "      <td>-0.205705</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.061633</td>\n",
       "      <td>0.242849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.209945</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.195584</td>\n",
       "      <td>0.103309</td>\n",
       "      <td>0.181790</td>\n",
       "      <td>-1.178892</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.074793</td>\n",
       "      <td>0.139667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.101027</td>\n",
       "      <td>-0.046854</td>\n",
       "      <td>-0.017241</td>\n",
       "      <td>0.137585</td>\n",
       "      <td>0.189559</td>\n",
       "      <td>0.045670</td>\n",
       "      <td>0.044319</td>\n",
       "      <td>0.041827</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000910</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.116357</td>\n",
       "      <td>-0.054528</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.110996</td>\n",
       "      <td>0.058416</td>\n",
       "      <td>0.028560</td>\n",
       "      <td>-0.042030</td>\n",
       "      <td>-0.029698</td>\n",
       "      <td>0.123479</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.034205</td>\n",
       "      <td>-0.330294</td>\n",
       "      <td>-0.059827</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.029642</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000915</td>\n",
       "      <td>0.011687</td>\n",
       "      <td>-0.081818</td>\n",
       "      <td>-0.135298</td>\n",
       "      <td>-0.093454</td>\n",
       "      <td>-0.010699</td>\n",
       "      <td>-0.039888</td>\n",
       "      <td>-0.073715</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.185120</td>\n",
       "      <td>0.051403</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.182431</td>\n",
       "      <td>-0.182527</td>\n",
       "      <td>-0.056837</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.104051</td>\n",
       "      <td>0.013638</td>\n",
       "      <td>0.109599</td>\n",
       "      <td>-0.013597</td>\n",
       "      <td>0.043204</td>\n",
       "      <td>-0.131804</td>\n",
       "      <td>0.011014</td>\n",
       "      <td>0.034395</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.008471</td>\n",
       "      <td>0.032560</td>\n",
       "      <td>0.018580</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.033978</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.142016</td>\n",
       "      <td>-0.052706</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.079782</td>\n",
       "      <td>-0.094637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.070320</td>\n",
       "      <td>0.045956</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.009296</td>\n",
       "      <td>-0.059030</td>\n",
       "      <td>-0.177046</td>\n",
       "      <td>-0.066809</td>\n",
       "      <td>-0.167655</td>\n",
       "      <td>-0.101921</td>\n",
       "      <td>0.039961</td>\n",
       "      <td>0.031024</td>\n",
       "      <td>-0.100145</td>\n",
       "      <td>0.081337</td>\n",
       "      <td>-0.014054</td>\n",
       "      <td>0.018068</td>\n",
       "      <td>-0.079056</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.082159</td>\n",
       "      <td>0.323352</td>\n",
       "      <td>0.291514</td>\n",
       "      <td>0.219518</td>\n",
       "      <td>0.174486</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.519119</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.405733</td>\n",
       "      <td>-0.437118</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.078440</td>\n",
       "      <td>0.004398</td>\n",
       "      <td>-0.742281</td>\n",
       "      <td>0.047431</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.746177</td>\n",
       "      <td>0.752573</td>\n",
       "      <td>0.550012</td>\n",
       "      <td>-0.677971</td>\n",
       "      <td>0.074731</td>\n",
       "      <td>0.110221</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.348750</td>\n",
       "      <td>0.810286</td>\n",
       "      <td>-0.559510</td>\n",
       "      <td>0.170530</td>\n",
       "      <td>-0.785275</td>\n",
       "      <td>0.072480</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.211176</td>\n",
       "      <td>0.440943</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.730199</td>\n",
       "      <td>-1.458310</td>\n",
       "      <td>-0.370210</td>\n",
       "      <td>0.126059</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.427525</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.076441</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750385</td>\n",
       "      <td>0.225542</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.996018</td>\n",
       "      <td>-0.230358</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.408191</td>\n",
       "      <td>-0.497723</td>\n",
       "      <td>0.544022</td>\n",
       "      <td>1.660275</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.562414</td>\n",
       "      <td>0.147210</td>\n",
       "      <td>0.093395</td>\n",
       "      <td>0.076219</td>\n",
       "      <td>-0.054184</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.006358</td>\n",
       "      <td>-0.097322</td>\n",
       "      <td>0.075266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.076700</td>\n",
       "      <td>0.115939</td>\n",
       "      <td>0.084768</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.060193</td>\n",
       "      <td>-0.001961</td>\n",
       "      <td>0.031119</td>\n",
       "      <td>0.020612</td>\n",
       "      <td>0.039432</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.002092</td>\n",
       "      <td>-0.056084</td>\n",
       "      <td>0.004733</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.229213</td>\n",
       "      <td>-0.431493</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.087996</td>\n",
       "      <td>-0.500464</td>\n",
       "      <td>0.104448</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.004199</td>\n",
       "      <td>0.144107</td>\n",
       "      <td>0.127515</td>\n",
       "      <td>-0.190637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.084160</td>\n",
       "      <td>0.276194</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.248013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.208443</td>\n",
       "      <td>0.141962</td>\n",
       "      <td>0.184243</td>\n",
       "      <td>-0.833693</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.085700</td>\n",
       "      <td>0.147333</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>-0.082857</td>\n",
       "      <td>-0.030072</td>\n",
       "      <td>-0.010687</td>\n",
       "      <td>0.159998</td>\n",
       "      <td>0.201732</td>\n",
       "      <td>0.055243</td>\n",
       "      <td>0.054178</td>\n",
       "      <td>0.053701</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.105131</td>\n",
       "      <td>-0.047380</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.101101</td>\n",
       "      <td>0.061992</td>\n",
       "      <td>0.032139</td>\n",
       "      <td>-0.041652</td>\n",
       "      <td>-0.029181</td>\n",
       "      <td>0.137426</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.026245</td>\n",
       "      <td>-0.238960</td>\n",
       "      <td>-0.056877</td>\n",
       "      <td>0.003318</td>\n",
       "      <td>0.008868</td>\n",
       "      <td>-0.021544</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001706</td>\n",
       "      <td>0.027953</td>\n",
       "      <td>-0.076381</td>\n",
       "      <td>-0.131513</td>\n",
       "      <td>-0.086090</td>\n",
       "      <td>-0.005317</td>\n",
       "      <td>-0.035972</td>\n",
       "      <td>-0.064462</td>\n",
       "      <td>0.016163</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.173527</td>\n",
       "      <td>0.069345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.193248</td>\n",
       "      <td>-0.174610</td>\n",
       "      <td>-0.051692</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.106645</td>\n",
       "      <td>0.015714</td>\n",
       "      <td>0.115191</td>\n",
       "      <td>-0.010783</td>\n",
       "      <td>0.047893</td>\n",
       "      <td>-0.124276</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.084831</td>\n",
       "      <td>0.012668</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.093968</td>\n",
       "      <td>0.078814</td>\n",
       "      <td>0.044579</td>\n",
       "      <td>0.074423</td>\n",
       "      <td>0.012568</td>\n",
       "      <td>-0.117574</td>\n",
       "      <td>-0.028076</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.075529</td>\n",
       "      <td>-0.090036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.071852</td>\n",
       "      <td>0.057240</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015557</td>\n",
       "      <td>-0.020083</td>\n",
       "      <td>-0.134122</td>\n",
       "      <td>-0.023133</td>\n",
       "      <td>-0.124083</td>\n",
       "      <td>-0.060258</td>\n",
       "      <td>0.061284</td>\n",
       "      <td>0.054757</td>\n",
       "      <td>-0.052682</td>\n",
       "      <td>0.105074</td>\n",
       "      <td>-0.001312</td>\n",
       "      <td>0.023673</td>\n",
       "      <td>-0.076166</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.096569</td>\n",
       "      <td>0.340873</td>\n",
       "      <td>0.313364</td>\n",
       "      <td>0.250039</td>\n",
       "      <td>0.223505</td>\n",
       "      <td>0.054587</td>\n",
       "      <td>-0.384559</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.915186</td>\n",
       "      <td>-0.010607</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-0.066523</td>\n",
       "      <td>0.007054</td>\n",
       "      <td>-0.739281</td>\n",
       "      <td>0.047551</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.883506</td>\n",
       "      <td>0.834756</td>\n",
       "      <td>0.613879</td>\n",
       "      <td>-0.231829</td>\n",
       "      <td>0.083096</td>\n",
       "      <td>0.157464</td>\n",
       "      <td>0.302858</td>\n",
       "      <td>-1.301492</td>\n",
       "      <td>0.981821</td>\n",
       "      <td>-0.473291</td>\n",
       "      <td>0.294498</td>\n",
       "      <td>-0.447184</td>\n",
       "      <td>0.114688</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.011911</td>\n",
       "      <td>0.470782</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.639471</td>\n",
       "      <td>-1.441796</td>\n",
       "      <td>-0.195057</td>\n",
       "      <td>0.135709</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.385876</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.163726</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.892602</td>\n",
       "      <td>0.265095</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.132646</td>\n",
       "      <td>-0.045628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.307605</td>\n",
       "      <td>-0.407779</td>\n",
       "      <td>0.577644</td>\n",
       "      <td>1.704767</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002154</td>\n",
       "      <td>-1.425117</td>\n",
       "      <td>0.164782</td>\n",
       "      <td>0.110971</td>\n",
       "      <td>0.093554</td>\n",
       "      <td>-0.040935</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.010294</td>\n",
       "      <td>-0.092941</td>\n",
       "      <td>0.075696</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.083474</td>\n",
       "      <td>0.136998</td>\n",
       "      <td>0.108099</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.044118</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.039013</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.045074</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.054269</td>\n",
       "      <td>0.016150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.225502</td>\n",
       "      <td>-0.426447</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.122282</td>\n",
       "      <td>-0.065406</td>\n",
       "      <td>0.137692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.220636</td>\n",
       "      <td>0.200314</td>\n",
       "      <td>-0.133097</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.097191</td>\n",
       "      <td>0.313401</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.267868</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.229869</td>\n",
       "      <td>0.226872</td>\n",
       "      <td>0.185077</td>\n",
       "      <td>-0.092453</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.093222</td>\n",
       "      <td>0.150152</td>\n",
       "      <td>0.015308</td>\n",
       "      <td>-0.036883</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.006059</td>\n",
       "      <td>0.195716</td>\n",
       "      <td>0.238788</td>\n",
       "      <td>0.082877</td>\n",
       "      <td>0.073141</td>\n",
       "      <td>0.064920</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.096411</td>\n",
       "      <td>-0.026498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.077284</td>\n",
       "      <td>0.065807</td>\n",
       "      <td>0.035744</td>\n",
       "      <td>-0.036596</td>\n",
       "      <td>-0.026644</td>\n",
       "      <td>0.142723</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001031</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.001253</td>\n",
       "      <td>-0.008050</td>\n",
       "      <td>-0.044671</td>\n",
       "      <td>0.009559</td>\n",
       "      <td>0.016200</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002156</td>\n",
       "      <td>0.032330</td>\n",
       "      <td>-0.059974</td>\n",
       "      <td>-0.120439</td>\n",
       "      <td>-0.066362</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.019755</td>\n",
       "      <td>-0.037250</td>\n",
       "      <td>0.024438</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.142766</td>\n",
       "      <td>0.075121</td>\n",
       "      <td>0.004952</td>\n",
       "      <td>0.197441</td>\n",
       "      <td>-0.153434</td>\n",
       "      <td>-0.034419</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.109659</td>\n",
       "      <td>0.016882</td>\n",
       "      <td>0.117625</td>\n",
       "      <td>-0.000857</td>\n",
       "      <td>0.049938</td>\n",
       "      <td>-0.099975</td>\n",
       "      <td>0.014260</td>\n",
       "      <td>0.101477</td>\n",
       "      <td>0.020143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.127298</td>\n",
       "      <td>0.123256</td>\n",
       "      <td>0.087761</td>\n",
       "      <td>0.115523</td>\n",
       "      <td>0.050656</td>\n",
       "      <td>-0.097624</td>\n",
       "      <td>-0.007588</td>\n",
       "      <td>0.028604</td>\n",
       "      <td>-0.070977</td>\n",
       "      <td>-0.075494</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.073611</td>\n",
       "      <td>0.060345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.024089</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.099260</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.093374</td>\n",
       "      <td>-0.034633</td>\n",
       "      <td>0.084855</td>\n",
       "      <td>0.072500</td>\n",
       "      <td>-0.014304</td>\n",
       "      <td>0.121161</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032163</td>\n",
       "      <td>-0.056445</td>\n",
       "      <td>0.002783</td>\n",
       "      <td>0.101291</td>\n",
       "      <td>0.344555</td>\n",
       "      <td>0.317840</td>\n",
       "      <td>0.256892</td>\n",
       "      <td>0.236159</td>\n",
       "      <td>0.072968</td>\n",
       "      <td>-0.069395</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.050346</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008829</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.047777</td>\n",
       "      <td>0.077751</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.006445</td>\n",
       "      <td>0.902544</td>\n",
       "      <td>0.672530</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.320492</td>\n",
       "      <td>0.196954</td>\n",
       "      <td>0.543557</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.093886</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.381800</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.144339</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.514372</td>\n",
       "      <td>0.026301</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.207573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.192483</td>\n",
       "      <td>0.213270</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.994652</td>\n",
       "      <td>0.355275</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.255332</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.590819</td>\n",
       "      <td>1.815396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.088150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.172730</td>\n",
       "      <td>0.118799</td>\n",
       "      <td>0.101339</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.016024</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.076634</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.088211</td>\n",
       "      <td>0.149236</td>\n",
       "      <td>0.121290</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.028808</td>\n",
       "      <td>0.043796</td>\n",
       "      <td>0.035595</td>\n",
       "      <td>0.053054</td>\n",
       "      <td>0.000976</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.024479</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.141310</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.154904</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.258326</td>\n",
       "      <td>0.234011</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.102978</td>\n",
       "      <td>0.342281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.283069</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.255506</td>\n",
       "      <td>0.300576</td>\n",
       "      <td>0.186445</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.100770</td>\n",
       "      <td>0.155144</td>\n",
       "      <td>0.020107</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.217509</td>\n",
       "      <td>0.260837</td>\n",
       "      <td>0.099298</td>\n",
       "      <td>0.084605</td>\n",
       "      <td>0.073014</td>\n",
       "      <td>0.005188</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.067599</td>\n",
       "      <td>0.037558</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.145623</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001989</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012930</td>\n",
       "      <td>0.019704</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003650</td>\n",
       "      <td>0.034730</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.028573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078362</td>\n",
       "      <td>0.013277</td>\n",
       "      <td>0.199830</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000815</td>\n",
       "      <td>0.111663</td>\n",
       "      <td>0.018212</td>\n",
       "      <td>0.119504</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.051608</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015347</td>\n",
       "      <td>0.110601</td>\n",
       "      <td>0.023935</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.137959</td>\n",
       "      <td>0.139141</td>\n",
       "      <td>0.103675</td>\n",
       "      <td>0.130437</td>\n",
       "      <td>0.066252</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.044229</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.078346</td>\n",
       "      <td>0.062821</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030247</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.102287</td>\n",
       "      <td>0.096802</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.144895</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.056156</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025337</td>\n",
       "      <td>0.122638</td>\n",
       "      <td>0.363660</td>\n",
       "      <td>0.334387</td>\n",
       "      <td>0.270292</td>\n",
       "      <td>0.248648</td>\n",
       "      <td>0.085175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        playoffs  shot_distance  last_5_sec_in_period  home_play  \\\n",
       "count  40.000000      40.000000             40.000000  40.000000   \n",
       "mean   -0.067308       0.003238             -0.719099   0.045846   \n",
       "std     0.024175       0.005957              0.119921   0.007599   \n",
       "min    -0.083360      -0.024615             -0.752796   0.000000   \n",
       "25%    -0.081405       0.001468             -0.746102   0.047256   \n",
       "50%    -0.078440       0.004398             -0.742281   0.047431   \n",
       "75%    -0.066523       0.007054             -0.739281   0.047551   \n",
       "max     0.000000       0.008829              0.000000   0.047777   \n",
       "\n",
       "       action_type_Alley Oop Dunk Shot  action_type_Alley Oop Layup shot  \\\n",
       "count                        40.000000                         40.000000   \n",
       "mean                          0.005154                         -0.007500   \n",
       "std                           0.016544                          0.018458   \n",
       "min                           0.000000                         -0.077141   \n",
       "25%                           0.000000                          0.000000   \n",
       "50%                           0.000000                          0.000000   \n",
       "75%                           0.000000                          0.000000   \n",
       "max                           0.077751                          0.000000   \n",
       "\n",
       "       action_type_Driving Dunk Shot  \\\n",
       "count                      40.000000   \n",
       "mean                        0.650134   \n",
       "std                         0.310007   \n",
       "min                         0.000000   \n",
       "25%                         0.522413   \n",
       "50%                         0.746177   \n",
       "75%                         0.883506   \n",
       "max                         1.006445   \n",
       "\n",
       "       action_type_Driving Finger Roll Layup Shot  \\\n",
       "count                                   40.000000   \n",
       "mean                                     0.631561   \n",
       "std                                      0.289486   \n",
       "min                                      0.000000   \n",
       "25%                                      0.530500   \n",
       "50%                                      0.752573   \n",
       "75%                                      0.834756   \n",
       "max                                      0.902544   \n",
       "\n",
       "       action_type_Driving Finger Roll Shot  action_type_Driving Jump shot  \\\n",
       "count                             40.000000                      40.000000   \n",
       "mean                               0.460566                      -0.535076   \n",
       "std                                0.217789                       0.330806   \n",
       "min                                0.000000                      -0.906305   \n",
       "25%                                0.379979                      -0.801146   \n",
       "50%                                0.550012                      -0.677971   \n",
       "75%                                0.613879                      -0.231829   \n",
       "max                                0.672530                       0.000000   \n",
       "\n",
       "       action_type_Driving Layup Shot  action_type_Driving Reverse Layup Shot  \\\n",
       "count                       40.000000                               40.000000   \n",
       "mean                         0.082582                                0.092887   \n",
       "std                          0.060448                                0.073139   \n",
       "min                          0.000000                                0.000000   \n",
       "25%                          0.044796                                0.006824   \n",
       "50%                          0.074731                                0.110221   \n",
       "75%                          0.083096                                0.157464   \n",
       "max                          0.320492                                0.196954   \n",
       "\n",
       "       action_type_Driving Slam Dunk Shot  action_type_Dunk Shot  \\\n",
       "count                           40.000000              40.000000   \n",
       "mean                             0.146879              -1.237399   \n",
       "std                              0.186366               0.322674   \n",
       "min                              0.000000              -1.384945   \n",
       "25%                              0.000000              -1.363549   \n",
       "50%                              0.000000              -1.348750   \n",
       "75%                              0.302858              -1.301492   \n",
       "max                              0.543557               0.000000   \n",
       "\n",
       "       action_type_Fadeaway Bank shot  action_type_Fadeaway Jump Shot  \\\n",
       "count                       40.000000                       40.000000   \n",
       "mean                         0.669684                       -0.510890   \n",
       "std                          0.383868                        0.138098   \n",
       "min                          0.000000                       -0.634440   \n",
       "25%                          0.460835                       -0.582212   \n",
       "50%                          0.810286                       -0.559510   \n",
       "75%                          0.981821                       -0.473291   \n",
       "max                          1.093886                        0.000000   \n",
       "\n",
       "       action_type_Finger Roll Layup Shot  action_type_Finger Roll Shot  \\\n",
       "count                           40.000000                     40.000000   \n",
       "mean                             0.162201                     -0.629970   \n",
       "std                              0.146379                      0.346350   \n",
       "min                              0.000000                     -0.986358   \n",
       "25%                              0.000000                     -0.891044   \n",
       "50%                              0.170530                     -0.785275   \n",
       "75%                              0.294498                     -0.447184   \n",
       "max                              0.381800                      0.000000   \n",
       "\n",
       "       action_type_Floating Jump shot  action_type_Follow Up Dunk Shot  \\\n",
       "count                       40.000000                             40.0   \n",
       "mean                         0.066927                              0.0   \n",
       "std                          0.050696                              0.0   \n",
       "min                          0.000000                              0.0   \n",
       "25%                          0.003367                              0.0   \n",
       "50%                          0.072480                              0.0   \n",
       "75%                          0.114688                              0.0   \n",
       "max                          0.144339                              0.0   \n",
       "\n",
       "       action_type_Hook Shot  action_type_Jump Bank Shot  \\\n",
       "count              40.000000                   40.000000   \n",
       "mean               -1.058261                    0.420556   \n",
       "std                 0.352595                    0.095808   \n",
       "min                -1.319788                    0.000000   \n",
       "25%                -1.243990                    0.407514   \n",
       "50%                -1.211176                    0.440943   \n",
       "75%                -1.011911                    0.470782   \n",
       "max                 0.000000                    0.514372   \n",
       "\n",
       "       action_type_Jump Hook Shot  action_type_Jump Shot  \\\n",
       "count                   40.000000              40.000000   \n",
       "mean                     0.001568              -1.653246   \n",
       "std                      0.005273               0.287245   \n",
       "min                      0.000000              -1.806051   \n",
       "25%                      0.000000              -1.749114   \n",
       "50%                      0.000000              -1.730199   \n",
       "75%                      0.000000              -1.639471   \n",
       "max                      0.026301               0.000000   \n",
       "\n",
       "       action_type_Layup Shot  action_type_Other  \\\n",
       "count               40.000000          40.000000   \n",
       "mean                -1.398728          -0.289802   \n",
       "std                  0.245723           0.158510   \n",
       "min                 -1.517654          -0.457941   \n",
       "25%                 -1.480952          -0.400540   \n",
       "50%                 -1.458310          -0.370210   \n",
       "75%                 -1.441796          -0.195057   \n",
       "max                  0.000000           0.000000   \n",
       "\n",
       "       action_type_Pullup Jump shot  action_type_Putback Layup Shot  \\\n",
       "count                     40.000000                            40.0   \n",
       "mean                       0.113922                             0.0   \n",
       "std                        0.042905                             0.0   \n",
       "min                        0.000000                             0.0   \n",
       "25%                        0.080419                             0.0   \n",
       "50%                        0.126059                             0.0   \n",
       "75%                        0.135709                             0.0   \n",
       "max                        0.207573                             0.0   \n",
       "\n",
       "       action_type_Reverse Dunk Shot  action_type_Reverse Layup Shot  \\\n",
       "count                           40.0                       40.000000   \n",
       "mean                             0.0                       -0.377835   \n",
       "std                              0.0                        0.130736   \n",
       "min                              0.0                       -0.492492   \n",
       "25%                              0.0                       -0.441411   \n",
       "50%                              0.0                       -0.427525   \n",
       "75%                              0.0                       -0.385876   \n",
       "max                              0.0                        0.000000   \n",
       "\n",
       "       action_type_Reverse Slam Dunk Shot  action_type_Running Bank shot  \\\n",
       "count                           40.000000                      40.000000   \n",
       "mean                             0.013553                       0.084479   \n",
       "std                              0.042080                       0.081770   \n",
       "min                              0.000000                       0.000000   \n",
       "25%                              0.000000                       0.000000   \n",
       "50%                              0.000000                       0.076441   \n",
       "75%                              0.000000                       0.163726   \n",
       "max                              0.192483                       0.213270   \n",
       "\n",
       "       action_type_Running Dunk Shot  action_type_Running Hook Shot  \\\n",
       "count                           40.0                      40.000000   \n",
       "mean                             0.0                       0.623469   \n",
       "std                              0.0                       0.343150   \n",
       "min                              0.0                       0.000000   \n",
       "25%                              0.0                       0.462241   \n",
       "50%                              0.0                       0.750385   \n",
       "75%                              0.0                       0.892602   \n",
       "max                              0.0                       0.994652   \n",
       "\n",
       "       action_type_Running Jump Shot  action_type_Running Layup Shot  \\\n",
       "count                      40.000000                            40.0   \n",
       "mean                        0.224786                             0.0   \n",
       "std                         0.059780                             0.0   \n",
       "min                         0.000000                             0.0   \n",
       "25%                         0.182808                             0.0   \n",
       "50%                         0.225542                             0.0   \n",
       "75%                         0.265095                             0.0   \n",
       "max                         0.355275                             0.0   \n",
       "\n",
       "       action_type_Slam Dunk Shot  action_type_Step Back Jump shot  \\\n",
       "count                   40.000000                        40.000000   \n",
       "mean                     0.882215                        -0.181078   \n",
       "std                      0.351699                         0.117541   \n",
       "min                      0.000000                        -0.337377   \n",
       "25%                      0.774243                        -0.261163   \n",
       "50%                      0.996018                        -0.230358   \n",
       "75%                      1.132646                        -0.045628   \n",
       "max                      1.255332                         0.000000   \n",
       "\n",
       "       action_type_Tip Shot  action_type_Turnaround Bank shot  \\\n",
       "count                  40.0                              40.0   \n",
       "mean                    0.0                               0.0   \n",
       "std                     0.0                               0.0   \n",
       "min                     0.0                               0.0   \n",
       "25%                     0.0                               0.0   \n",
       "50%                     0.0                               0.0   \n",
       "75%                     0.0                               0.0   \n",
       "max                     0.0                               0.0   \n",
       "\n",
       "       action_type_Turnaround Fadeaway shot  action_type_Turnaround Jump Shot  \\\n",
       "count                             40.000000                         40.000000   \n",
       "mean                              -0.357021                         -0.447970   \n",
       "std                                0.128954                          0.136443   \n",
       "min                               -0.485843                         -0.573056   \n",
       "25%                               -0.426768                         -0.517805   \n",
       "50%                               -0.408191                         -0.497723   \n",
       "75%                               -0.307605                         -0.407779   \n",
       "max                                0.000000                          0.000000   \n",
       "\n",
       "       combined_shot_type_Bank Shot  combined_shot_type_Dunk  \\\n",
       "count                     40.000000                40.000000   \n",
       "mean                       0.485737                 1.629238   \n",
       "std                        0.163263                 0.273754   \n",
       "min                        0.000000                 0.000000   \n",
       "25%                        0.504212                 1.628425   \n",
       "50%                        0.544022                 1.660275   \n",
       "75%                        0.577644                 1.704767   \n",
       "max                        0.590819                 1.815396   \n",
       "\n",
       "       combined_shot_type_Hook Shot  combined_shot_type_Jump Shot  \\\n",
       "count                          40.0                          40.0   \n",
       "mean                            0.0                           0.0   \n",
       "std                             0.0                           0.0   \n",
       "min                             0.0                           0.0   \n",
       "25%                             0.0                           0.0   \n",
       "50%                             0.0                           0.0   \n",
       "75%                             0.0                           0.0   \n",
       "max                             0.0                           0.0   \n",
       "\n",
       "       combined_shot_type_Layup  combined_shot_type_Tip Shot   period_1  \\\n",
       "count                 40.000000                    40.000000  40.000000   \n",
       "mean                   0.010910                    -1.428047   0.131309   \n",
       "std                    0.022953                     0.350530   0.043514   \n",
       "min                    0.000000                    -1.638497   0.000000   \n",
       "25%                    0.000000                    -1.577479   0.114757   \n",
       "50%                    0.000000                    -1.562414   0.147210   \n",
       "75%                    0.002154                    -1.425117   0.164782   \n",
       "max                    0.088150                     0.000000   0.172730   \n",
       "\n",
       "        period_2   period_3   period_4  period_5  period_6  period_7  \\\n",
       "count  40.000000  40.000000  40.000000      40.0      40.0      40.0   \n",
       "mean    0.078813   0.063650  -0.063605       0.0       0.0       0.0   \n",
       "std     0.040139   0.036309   0.030661       0.0       0.0       0.0   \n",
       "min     0.000000   0.000000  -0.125557       0.0       0.0       0.0   \n",
       "25%     0.061710   0.045569  -0.082135       0.0       0.0       0.0   \n",
       "50%     0.093395   0.076219  -0.054184       0.0       0.0       0.0   \n",
       "75%     0.110971   0.093554  -0.040935       0.0       0.0       0.0   \n",
       "max     0.118799   0.101339   0.000000       0.0       0.0       0.0   \n",
       "\n",
       "       season_1996-97  season_1997-98  season_1998-99  season_1999-00  \\\n",
       "count       40.000000       40.000000       40.000000            40.0   \n",
       "mean         0.006509       -0.088745        0.064861             0.0   \n",
       "std          0.005399        0.025019        0.022308             0.0   \n",
       "min          0.000000       -0.102067        0.000000             0.0   \n",
       "25%          0.000000       -0.099508        0.068965             0.0   \n",
       "50%          0.006358       -0.097322        0.075266             0.0   \n",
       "75%          0.010294       -0.092941        0.075696             0.0   \n",
       "max          0.016024        0.000000        0.076634             0.0   \n",
       "\n",
       "       season_2000-01  season_2001-02  season_2002-03  season_2003-04  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.067250        0.094410        0.069968       -0.002168   \n",
       "std          0.022799        0.052169        0.043379        0.004231   \n",
       "min          0.000000        0.000000        0.000000       -0.013460   \n",
       "25%          0.058583        0.061840        0.035543       -0.001128   \n",
       "50%          0.076700        0.115939        0.084768        0.000000   \n",
       "75%          0.083474        0.136998        0.108099        0.000000   \n",
       "max          0.088211        0.149236        0.121290        0.000000   \n",
       "\n",
       "       season_2004-05  season_2005-06  season_2006-07  season_2007-08  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean        -0.058171       -0.015736        0.026751        0.017283   \n",
       "std          0.031107        0.023448        0.013815        0.011950   \n",
       "min         -0.096206       -0.055219        0.000000        0.000000   \n",
       "25%         -0.083879       -0.037408        0.014480        0.005364   \n",
       "50%         -0.060193       -0.001961        0.031119        0.020612   \n",
       "75%         -0.044118        0.000000        0.039013        0.027794   \n",
       "max          0.000000        0.028808        0.043796        0.035595   \n",
       "\n",
       "       season_2008-09  season_2009-10  season_2010-11  season_2011-12  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.037092        0.000059       -0.001977       -0.052236   \n",
       "std          0.011251        0.000196        0.001919        0.013374   \n",
       "min          0.000000        0.000000       -0.005985       -0.058976   \n",
       "25%          0.031289        0.000000       -0.003286       -0.057267   \n",
       "50%          0.039432        0.000000       -0.002092       -0.056084   \n",
       "75%          0.045074        0.000000        0.000000       -0.054269   \n",
       "max          0.053054        0.000976        0.000000        0.000000   \n",
       "\n",
       "       season_2012-13  season_2013-14  season_2014-15  season_2015-16  \\\n",
       "count       40.000000            40.0       40.000000       40.000000   \n",
       "mean         0.008240             0.0       -0.214846       -0.417950   \n",
       "std          0.009051             0.0        0.053138        0.073279   \n",
       "min          0.000000             0.0       -0.241164       -0.451475   \n",
       "25%          0.000000             0.0       -0.233924       -0.438684   \n",
       "50%          0.004733             0.0       -0.229213       -0.431493   \n",
       "75%          0.016150             0.0       -0.225502       -0.426447   \n",
       "max          0.024479             0.0        0.000000        0.000000   \n",
       "\n",
       "       shot_type_2PT Field Goal  shot_type_3PT Field Goal  \\\n",
       "count                      40.0                 40.000000   \n",
       "mean                        0.0                  0.071969   \n",
       "std                         0.0                  0.054553   \n",
       "min                         0.0                  0.000000   \n",
       "25%                         0.0                  0.000000   \n",
       "50%                         0.0                  0.087996   \n",
       "75%                         0.0                  0.122282   \n",
       "max                         0.0                  0.141310   \n",
       "\n",
       "       shot_zone_area_Back Court(BC)  shot_zone_area_Center(C)  \\\n",
       "count                      40.000000                 40.000000   \n",
       "mean                       -0.625135                  0.111434   \n",
       "std                         0.587678                  0.031290   \n",
       "min                        -1.931117                  0.000000   \n",
       "25%                        -1.016420                  0.093909   \n",
       "50%                        -0.500464                  0.104448   \n",
       "75%                        -0.065406                  0.137692   \n",
       "max                         0.000000                  0.154904   \n",
       "\n",
       "       shot_zone_area_Left Side Center(LC)  shot_zone_area_Left Side(L)  \\\n",
       "count                                 40.0                    40.000000   \n",
       "mean                                   0.0                    -0.005075   \n",
       "std                                    0.0                     0.005270   \n",
       "min                                    0.0                    -0.015173   \n",
       "25%                                    0.0                    -0.009619   \n",
       "50%                                    0.0                    -0.004199   \n",
       "75%                                    0.0                     0.000000   \n",
       "max                                    0.0                     0.000000   \n",
       "\n",
       "       shot_zone_area_Right Side Center(RC)  shot_zone_area_Right Side(R)  \\\n",
       "count                             40.000000                     40.000000   \n",
       "mean                               0.153678                      0.133665   \n",
       "std                                0.069472                      0.069466   \n",
       "min                                0.000000                      0.000000   \n",
       "25%                                0.096234                      0.083877   \n",
       "50%                                0.144107                      0.127515   \n",
       "75%                                0.220636                      0.200314   \n",
       "max                                0.258326                      0.234011   \n",
       "\n",
       "       shot_zone_basic_Above the Break 3  shot_zone_basic_Backcourt  \\\n",
       "count                          40.000000                       40.0   \n",
       "mean                           -0.159368                        0.0   \n",
       "std                             0.064823                        0.0   \n",
       "min                            -0.212588                        0.0   \n",
       "25%                            -0.205705                        0.0   \n",
       "50%                            -0.190637                        0.0   \n",
       "75%                            -0.133097                        0.0   \n",
       "max                             0.000000                        0.0   \n",
       "\n",
       "       shot_zone_basic_In The Paint (Non-RA)  shot_zone_basic_Left Corner 3  \\\n",
       "count                              40.000000                      40.000000   \n",
       "mean                                0.071976                       0.251864   \n",
       "std                                 0.033934                       0.092533   \n",
       "min                                 0.000000                       0.000000   \n",
       "25%                                 0.061633                       0.242849   \n",
       "50%                                 0.084160                       0.276194   \n",
       "75%                                 0.097191                       0.313401   \n",
       "max                                 0.102978                       0.342281   \n",
       "\n",
       "       shot_zone_basic_Mid-Range  shot_zone_basic_Restricted Area  \\\n",
       "count                       40.0                        40.000000   \n",
       "mean                         0.0                         0.217221   \n",
       "std                          0.0                         0.077590   \n",
       "min                          0.0                         0.000000   \n",
       "25%                          0.0                         0.209945   \n",
       "50%                          0.0                         0.248013   \n",
       "75%                          0.0                         0.267868   \n",
       "max                          0.0                         0.283069   \n",
       "\n",
       "       shot_zone_basic_Right Corner 3  shot_zone_range_16-24 ft.  \\\n",
       "count                            40.0                  40.000000   \n",
       "mean                              0.0                   0.202678   \n",
       "std                               0.0                   0.050515   \n",
       "min                               0.0                   0.000000   \n",
       "25%                               0.0                   0.195584   \n",
       "50%                               0.0                   0.208443   \n",
       "75%                               0.0                   0.229869   \n",
       "max                               0.0                   0.255506   \n",
       "\n",
       "       shot_zone_range_24+ ft.  shot_zone_range_8-16 ft.  \\\n",
       "count                40.000000                 40.000000   \n",
       "mean                  0.161808                  0.163149   \n",
       "std                   0.082146                  0.055753   \n",
       "min                   0.000000                  0.000000   \n",
       "25%                   0.103309                  0.181790   \n",
       "50%                   0.141962                  0.184243   \n",
       "75%                   0.226872                  0.185077   \n",
       "max                   0.300576                  0.186445   \n",
       "\n",
       "       shot_zone_range_Back Court Shot  shot_zone_range_Less Than 8 ft.  \\\n",
       "count                        40.000000                        40.000000   \n",
       "mean                         -0.808262                        -0.004243   \n",
       "std                           0.667419                         0.020314   \n",
       "min                          -2.109865                        -0.119578   \n",
       "25%                          -1.178892                         0.000000   \n",
       "50%                          -0.833693                         0.000000   \n",
       "75%                          -0.092453                         0.000000   \n",
       "max                           0.000000                         0.000000   \n",
       "\n",
       "       game_year_1996  game_year_1997  game_year_1998  game_year_1999  \\\n",
       "count            40.0            40.0            40.0       40.000000   \n",
       "mean              0.0             0.0             0.0        0.078732   \n",
       "std               0.0             0.0             0.0        0.024611   \n",
       "min               0.0             0.0             0.0        0.000000   \n",
       "25%               0.0             0.0             0.0        0.074793   \n",
       "50%               0.0             0.0             0.0        0.085700   \n",
       "75%               0.0             0.0             0.0        0.093222   \n",
       "max               0.0             0.0             0.0        0.100770   \n",
       "\n",
       "       game_year_2000  game_year_2001  game_year_2002  game_year_2003  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.135902        0.005563       -0.066045       -0.024721   \n",
       "std          0.031724        0.007400        0.039377        0.022053   \n",
       "min          0.000000        0.000000       -0.107593       -0.052853   \n",
       "25%          0.139667        0.000000       -0.101027       -0.046854   \n",
       "50%          0.147333        0.000274       -0.082857       -0.030072   \n",
       "75%          0.150152        0.015308       -0.036883        0.000000   \n",
       "max          0.155144        0.020107        0.000000        0.000000   \n",
       "\n",
       "       game_year_2004  game_year_2005  game_year_2006  game_year_2007  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean        -0.012824        0.153404        0.201618        0.059015   \n",
       "std          0.010620        0.057814        0.053122        0.029089   \n",
       "min         -0.039895        0.000000        0.000000        0.000000   \n",
       "25%         -0.017241        0.137585        0.189559        0.045670   \n",
       "50%         -0.010687        0.159998        0.201732        0.055243   \n",
       "75%         -0.006059        0.195716        0.238788        0.082877   \n",
       "max          0.000000        0.217509        0.260837        0.099298   \n",
       "\n",
       "       game_year_2008  game_year_2009  game_year_2010  game_year_2011  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.054311        0.048892        0.000670       -0.000620   \n",
       "std          0.023657        0.022011        0.001637        0.001003   \n",
       "min          0.000000        0.000000        0.000000       -0.003285   \n",
       "25%          0.044319        0.041827        0.000000       -0.000910   \n",
       "50%          0.054178        0.053701        0.000000        0.000000   \n",
       "75%          0.073141        0.064920        0.000000        0.000000   \n",
       "max          0.084605        0.073014        0.005188        0.000000   \n",
       "\n",
       "       game_year_2012  game_year_2013  game_year_2014  game_year_2015  \\\n",
       "count            40.0       40.000000       40.000000            40.0   \n",
       "mean              0.0       -0.097646       -0.037951             0.0   \n",
       "std               0.0        0.029843        0.020758             0.0   \n",
       "min               0.0       -0.121747       -0.057326             0.0   \n",
       "25%               0.0       -0.116357       -0.054528             0.0   \n",
       "50%               0.0       -0.105131       -0.047380             0.0   \n",
       "75%               0.0       -0.096411       -0.026498             0.0   \n",
       "max               0.0        0.000000        0.000000             0.0   \n",
       "\n",
       "       game_year_2016  game_month_1  game_month_2  game_month_3  game_month_4  \\\n",
       "count       40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean        -0.086182      0.058367      0.030351     -0.036139     -0.025724   \n",
       "std          0.036097      0.014137      0.008347      0.011831      0.007968   \n",
       "min         -0.116345      0.000000      0.000000     -0.042875     -0.030287   \n",
       "25%         -0.110996      0.058416      0.028560     -0.042030     -0.029698   \n",
       "50%         -0.101101      0.061992      0.032139     -0.041652     -0.029181   \n",
       "75%         -0.077284      0.065807      0.035744     -0.036596     -0.026644   \n",
       "max          0.000000      0.067599      0.037558      0.000000      0.000000   \n",
       "\n",
       "       game_month_5  game_month_6  game_month_10  game_month_11  \\\n",
       "count     40.000000          40.0      40.000000      40.000000   \n",
       "mean       0.123732           0.0      -0.000180       0.000503   \n",
       "std        0.034914           0.0       0.000585       0.000670   \n",
       "min        0.000000           0.0      -0.002444       0.000000   \n",
       "25%        0.123479           0.0       0.000000       0.000000   \n",
       "50%        0.137426           0.0       0.000000       0.000000   \n",
       "75%        0.142723           0.0       0.000000       0.001031   \n",
       "max        0.145623           0.0       0.000000       0.001989   \n",
       "\n",
       "       game_month_12  opponent_ATL  opponent_BKN  opponent_BOS  opponent_CHA  \\\n",
       "count           40.0     40.000000     40.000000     40.000000     40.000000   \n",
       "mean             0.0     -0.020792     -0.197255     -0.047986      0.004730   \n",
       "std              0.0      0.014779      0.145011      0.019083      0.004969   \n",
       "min              0.0     -0.038113     -0.376066     -0.062038      0.000000   \n",
       "25%              0.0     -0.034205     -0.330294     -0.059827      0.000000   \n",
       "50%              0.0     -0.026245     -0.238960     -0.056877      0.003318   \n",
       "75%              0.0     -0.001253     -0.008050     -0.044671      0.009559   \n",
       "max              0.0      0.000000      0.000000      0.000000      0.012930   \n",
       "\n",
       "       opponent_CHI  opponent_CLE  opponent_DAL  opponent_DEN  opponent_DET  \\\n",
       "count     40.000000     40.000000          40.0     40.000000     40.000000   \n",
       "mean       0.008608     -0.017499           0.0      0.001548      0.021688   \n",
       "std        0.007772      0.013026           0.0      0.000963      0.013169   \n",
       "min        0.000000     -0.033496           0.0      0.000000      0.000000   \n",
       "25%        0.000000     -0.029642           0.0      0.000915      0.011687   \n",
       "50%        0.008868     -0.021544           0.0      0.001706      0.027953   \n",
       "75%        0.016200      0.000000           0.0      0.002156      0.032330   \n",
       "max        0.019704      0.000000           0.0      0.003650      0.034730   \n",
       "\n",
       "       opponent_GSW  opponent_HOU  opponent_IND  opponent_LAC  opponent_MEM  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean      -0.064887     -0.118666     -0.072942     -0.005428     -0.028353   \n",
       "std        0.025589      0.033027      0.030205      0.005180      0.015092   \n",
       "min       -0.084372     -0.137458     -0.097020     -0.013179     -0.041758   \n",
       "25%       -0.081818     -0.135298     -0.093454     -0.010699     -0.039888   \n",
       "50%       -0.076381     -0.131513     -0.086090     -0.005317     -0.035972   \n",
       "75%       -0.059974     -0.120439     -0.066362      0.000000     -0.019755   \n",
       "max        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "\n",
       "       opponent_MIA  opponent_MIL  opponent_MIN  opponent_NJN  opponent_NOH  \\\n",
       "count     40.000000     40.000000          40.0     40.000000     40.000000   \n",
       "mean      -0.052038      0.013917           0.0     -0.149935      0.057026   \n",
       "std        0.027606      0.011182           0.0      0.055223      0.026306   \n",
       "min       -0.078049      0.000000           0.0     -0.190368      0.000000   \n",
       "25%       -0.073715      0.000000           0.0     -0.185120      0.051403   \n",
       "50%       -0.064462      0.016163           0.0     -0.173527      0.069345   \n",
       "75%       -0.037250      0.024438           0.0     -0.142766      0.075121   \n",
       "max        0.000000      0.028573           0.0      0.000000      0.078362   \n",
       "\n",
       "       opponent_NOP  opponent_NYK  opponent_OKC  opponent_ORL  opponent_PHI  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean       0.002827      0.175643     -0.156082     -0.042050      0.000042   \n",
       "std        0.004509      0.047163      0.046583      0.020269      0.000167   \n",
       "min        0.000000      0.000000     -0.186536     -0.059513      0.000000   \n",
       "25%        0.000000      0.182431     -0.182527     -0.056837      0.000000   \n",
       "50%        0.000000      0.193248     -0.174610     -0.051692      0.000000   \n",
       "75%        0.004952      0.197441     -0.153434     -0.034419      0.000000   \n",
       "max        0.013277      0.199830      0.000000      0.000000      0.000815   \n",
       "\n",
       "       opponent_PHX  opponent_POR  opponent_SAC  opponent_SAS  opponent_SEA  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean       0.100322      0.013260      0.105569     -0.008531      0.041832   \n",
       "std        0.022442      0.005883      0.027341      0.005861      0.014831   \n",
       "min        0.000000      0.000000      0.000000     -0.015356      0.000000   \n",
       "25%        0.104051      0.013638      0.109599     -0.013597      0.043204   \n",
       "50%        0.106645      0.015714      0.115191     -0.010783      0.047893   \n",
       "75%        0.109659      0.016882      0.117625     -0.000857      0.049938   \n",
       "max        0.111663      0.018212      0.119504      0.000000      0.051608   \n",
       "\n",
       "       opponent_TOR  opponent_UTA  opponent_VAN  opponent_WAS  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000   \n",
       "mean      -0.105710      0.010890      0.067532      0.011230   \n",
       "std        0.041276      0.005238      0.041408      0.009353   \n",
       "min       -0.135916      0.000000      0.000000      0.000000   \n",
       "25%       -0.131804      0.011014      0.034395      0.000000   \n",
       "50%       -0.124276      0.013370      0.084831      0.012668   \n",
       "75%       -0.099975      0.014260      0.101477      0.020143   \n",
       "max        0.000000      0.015347      0.110601      0.023935   \n",
       "\n",
       "       loc_x_(-250.498, -230.08]  loc_x_(-230.08, -210.16]  \\\n",
       "count                  40.000000                 40.000000   \n",
       "mean                   -0.005857                  0.079179   \n",
       "std                     0.010591                  0.052004   \n",
       "min                    -0.033690                  0.000000   \n",
       "25%                    -0.008471                  0.032560   \n",
       "50%                     0.000000                  0.093968   \n",
       "75%                     0.000000                  0.127298   \n",
       "max                     0.000000                  0.137959   \n",
       "\n",
       "       loc_x_(-210.16, -190.24]  loc_x_(-190.24, -170.32]  \\\n",
       "count                 40.000000                 40.000000   \n",
       "mean                   0.071095                  0.045831   \n",
       "std                    0.052072                  0.040132   \n",
       "min                    0.000000                  0.000000   \n",
       "25%                    0.018580                  0.000000   \n",
       "50%                    0.078814                  0.044579   \n",
       "75%                    0.123256                  0.087761   \n",
       "max                    0.139141                  0.103675   \n",
       "\n",
       "       loc_x_(-170.32, -150.4]  loc_x_(-150.4, -130.48]  \\\n",
       "count                40.000000                40.000000   \n",
       "mean                  0.070516                 0.023871   \n",
       "std                   0.045664                 0.026142   \n",
       "min                   0.000000                 0.000000   \n",
       "25%                   0.033978                 0.000000   \n",
       "50%                   0.074423                 0.012568   \n",
       "75%                   0.115523                 0.050656   \n",
       "max                   0.130437                 0.066252   \n",
       "\n",
       "       loc_x_(-130.48, -110.56]  loc_x_(-110.56, -90.64]  \\\n",
       "count                 40.000000                40.000000   \n",
       "mean                  -0.113778                -0.029249   \n",
       "std                    0.033965                 0.021985   \n",
       "min                   -0.146263                -0.056858   \n",
       "25%                   -0.142016                -0.052706   \n",
       "50%                   -0.117574                -0.028076   \n",
       "75%                   -0.097624                -0.007588   \n",
       "max                    0.000000                 0.000000   \n",
       "\n",
       "       loc_x_(-90.64, -70.72]  loc_x_(-70.72, -50.8]  loc_x_(-50.8, -30.88]  \\\n",
       "count               40.000000              40.000000              40.000000   \n",
       "mean                 0.012963              -0.066040              -0.076743   \n",
       "std                  0.016887               0.025297               0.028952   \n",
       "min                  0.000000              -0.084593              -0.096894   \n",
       "25%                  0.000000              -0.079782              -0.094637   \n",
       "50%                  0.000000              -0.075529              -0.090036   \n",
       "75%                  0.028604              -0.070977              -0.075494   \n",
       "max                  0.044229               0.000000               0.000000   \n",
       "\n",
       "       loc_x_(-30.88, -10.96]  loc_x_(-10.96, 8.96]  loc_x_(8.96, 28.88]  \\\n",
       "count                    40.0             40.000000            40.000000   \n",
       "mean                      0.0              0.069959             0.048349   \n",
       "std                       0.0              0.011627             0.019603   \n",
       "min                       0.0              0.000000             0.000000   \n",
       "25%                       0.0              0.070320             0.045956   \n",
       "50%                       0.0              0.071852             0.057240   \n",
       "75%                       0.0              0.073611             0.060345   \n",
       "max                       0.0              0.078346             0.062821   \n",
       "\n",
       "       loc_x_(28.88, 48.8]  loc_x_(48.8, 68.72]  loc_x_(68.72, 88.64]  \\\n",
       "count                 40.0            40.000000             40.000000   \n",
       "mean                   0.0             0.016064             -0.029035   \n",
       "std                    0.0             0.009309              0.030483   \n",
       "min                    0.0             0.000000             -0.079199   \n",
       "25%                    0.0             0.009296             -0.059030   \n",
       "50%                    0.0             0.015557             -0.020083   \n",
       "75%                    0.0             0.024089              0.000000   \n",
       "max                    0.0             0.030247              0.000000   \n",
       "\n",
       "       loc_x_(88.64, 108.56]  loc_x_(108.56, 128.48]  loc_x_(128.48, 148.4]  \\\n",
       "count              40.000000               40.000000              40.000000   \n",
       "mean               -0.128454               -0.033072              -0.122116   \n",
       "std                 0.055897                0.034668               0.053097   \n",
       "min                -0.199490               -0.090931              -0.193177   \n",
       "25%                -0.177046               -0.066809              -0.167655   \n",
       "50%                -0.134122               -0.023133              -0.124083   \n",
       "75%                -0.099260                0.000000              -0.093374   \n",
       "max                 0.000000                0.000000               0.000000   \n",
       "\n",
       "       loc_x_(148.4, 168.32]  loc_x_(168.32, 188.24]  loc_x_(188.24, 208.16]  \\\n",
       "count              40.000000               40.000000               40.000000   \n",
       "mean               -0.064741                0.060070                0.051499   \n",
       "std                 0.041378                0.027891                0.027487   \n",
       "min                -0.128484                0.000000                0.000000   \n",
       "25%                -0.101921                0.039961                0.031024   \n",
       "50%                -0.060258                0.061284                0.054757   \n",
       "75%                -0.034633                0.084855                0.072500   \n",
       "max                 0.000000                0.102287                0.096802   \n",
       "\n",
       "       loc_x_(208.16, 228.08]  loc_x_(228.08, 248.0]  loc_y_(-44.835, -10.6]  \\\n",
       "count               40.000000              40.000000               40.000000   \n",
       "mean                -0.058648               0.093486               -0.006629   \n",
       "std                  0.047624               0.041751                0.007918   \n",
       "min                 -0.134694               0.000000               -0.022062   \n",
       "25%                 -0.100145               0.081337               -0.014054   \n",
       "50%                 -0.052682               0.105074               -0.001312   \n",
       "75%                 -0.014304               0.121161                0.000000   \n",
       "max                  0.000000               0.144895                0.000000   \n",
       "\n",
       "       loc_y_(-10.6, 22.8]  loc_y_(22.8, 56.2]  loc_y_(56.2, 89.6]  \\\n",
       "count            40.000000           40.000000           40.000000   \n",
       "mean              0.025924           -0.069691            0.005118   \n",
       "std               0.017052            0.016645            0.009212   \n",
       "min               0.000000           -0.087962            0.000000   \n",
       "25%               0.018068           -0.079056            0.000000   \n",
       "50%               0.023673           -0.076166            0.000000   \n",
       "75%               0.032163           -0.056445            0.002783   \n",
       "max               0.056156            0.000000            0.025337   \n",
       "\n",
       "       loc_y_(89.6, 123.0]  loc_y_(123.0, 156.4]  loc_y_(156.4, 189.8]  \\\n",
       "count            40.000000             40.000000             40.000000   \n",
       "mean              0.087115              0.319396              0.289124   \n",
       "std               0.032611              0.065882              0.065527   \n",
       "min               0.000000              0.000000              0.000000   \n",
       "25%               0.082159              0.323352              0.291514   \n",
       "50%               0.096569              0.340873              0.313364   \n",
       "75%               0.101291              0.344555              0.317840   \n",
       "max               0.122638              0.363660              0.334387   \n",
       "\n",
       "       loc_y_(189.8, 223.2]  loc_y_(223.2, 256.6]  loc_y_(256.6, 290.0]  \\\n",
       "count             40.000000             40.000000             40.000000   \n",
       "mean               0.221091              0.188956              0.043087   \n",
       "std                0.068413              0.075383              0.034134   \n",
       "min                0.000000              0.000000              0.000000   \n",
       "25%                0.219518              0.174486              0.000000   \n",
       "50%                0.250039              0.223505              0.054587   \n",
       "75%                0.256892              0.236159              0.072968   \n",
       "max                0.270292              0.248648              0.085175   \n",
       "\n",
       "       loc_y_(290.0, 323.4]  loc_y_(323.4, 356.8]  loc_y_(356.8, 390.2]  \\\n",
       "count             40.000000                  40.0             40.000000   \n",
       "mean              -0.321683                   0.0             -0.828901   \n",
       "std                0.223204                   0.0              0.639990   \n",
       "min               -0.592999                   0.0             -1.744994   \n",
       "25%               -0.519119                   0.0             -1.405733   \n",
       "50%               -0.384559                   0.0             -0.915186   \n",
       "75%               -0.069395                   0.0             -0.050346   \n",
       "max                0.000000                   0.0              0.000000   \n",
       "\n",
       "       loc_y_(390.2, 423.6]  loc_y_(423.6, 457.0]  loc_y_(457.0, 490.4]  \\\n",
       "count             40.000000                  40.0                  40.0   \n",
       "mean              -0.213861                   0.0                   0.0   \n",
       "std                0.266243                   0.0                   0.0   \n",
       "min               -0.749138                   0.0                   0.0   \n",
       "25%               -0.437118                   0.0                   0.0   \n",
       "50%               -0.010607                   0.0                   0.0   \n",
       "75%                0.000000                   0.0                   0.0   \n",
       "max                0.000000                   0.0                   0.0   \n",
       "\n",
       "       loc_y_(490.4, 523.8]  loc_y_(523.8, 557.2]  loc_y_(557.2, 590.6]  \\\n",
       "count                  40.0                  40.0                  40.0   \n",
       "mean                    0.0                   0.0                   0.0   \n",
       "std                     0.0                   0.0                   0.0   \n",
       "min                     0.0                   0.0                   0.0   \n",
       "25%                     0.0                   0.0                   0.0   \n",
       "50%                     0.0                   0.0                   0.0   \n",
       "75%                     0.0                   0.0                   0.0   \n",
       "max                     0.0                   0.0                   0.0   \n",
       "\n",
       "       loc_y_(590.6, 624.0]  loc_y_(624.0, 657.4]  loc_y_(657.4, 690.8]  \\\n",
       "count                  40.0                  40.0                  40.0   \n",
       "mean                    0.0                   0.0                   0.0   \n",
       "std                     0.0                   0.0                   0.0   \n",
       "min                     0.0                   0.0                   0.0   \n",
       "25%                     0.0                   0.0                   0.0   \n",
       "50%                     0.0                   0.0                   0.0   \n",
       "75%                     0.0                   0.0                   0.0   \n",
       "max                     0.0                   0.0                   0.0   \n",
       "\n",
       "       loc_y_(690.8, 724.2]  loc_y_(724.2, 757.6]  loc_y_(757.6, 791.0]  \n",
       "count                  40.0                  40.0                  40.0  \n",
       "mean                    0.0                   0.0                   0.0  \n",
       "std                     0.0                   0.0                   0.0  \n",
       "min                     0.0                   0.0                   0.0  \n",
       "25%                     0.0                   0.0                   0.0  \n",
       "50%                     0.0                   0.0                   0.0  \n",
       "75%                     0.0                   0.0                   0.0  \n",
       "max                     0.0                   0.0                   0.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Таблица статистических показателей для признаков с L1-регуляризацией')\n",
    "df_l1.T.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Таблица статистических показателей для признаков с L2-регуляризацией\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>playoffs</th>\n",
       "      <th>shot_distance</th>\n",
       "      <th>last_5_sec_in_period</th>\n",
       "      <th>home_play</th>\n",
       "      <th>action_type_Alley Oop Dunk Shot</th>\n",
       "      <th>action_type_Alley Oop Layup shot</th>\n",
       "      <th>action_type_Driving Dunk Shot</th>\n",
       "      <th>action_type_Driving Finger Roll Layup Shot</th>\n",
       "      <th>action_type_Driving Finger Roll Shot</th>\n",
       "      <th>action_type_Driving Jump shot</th>\n",
       "      <th>action_type_Driving Layup Shot</th>\n",
       "      <th>action_type_Driving Reverse Layup Shot</th>\n",
       "      <th>action_type_Driving Slam Dunk Shot</th>\n",
       "      <th>action_type_Dunk Shot</th>\n",
       "      <th>action_type_Fadeaway Bank shot</th>\n",
       "      <th>action_type_Fadeaway Jump Shot</th>\n",
       "      <th>action_type_Finger Roll Layup Shot</th>\n",
       "      <th>action_type_Finger Roll Shot</th>\n",
       "      <th>action_type_Floating Jump shot</th>\n",
       "      <th>action_type_Follow Up Dunk Shot</th>\n",
       "      <th>action_type_Hook Shot</th>\n",
       "      <th>action_type_Jump Bank Shot</th>\n",
       "      <th>action_type_Jump Hook Shot</th>\n",
       "      <th>action_type_Jump Shot</th>\n",
       "      <th>action_type_Layup Shot</th>\n",
       "      <th>action_type_Other</th>\n",
       "      <th>action_type_Pullup Jump shot</th>\n",
       "      <th>action_type_Putback Layup Shot</th>\n",
       "      <th>action_type_Reverse Dunk Shot</th>\n",
       "      <th>action_type_Reverse Layup Shot</th>\n",
       "      <th>action_type_Reverse Slam Dunk Shot</th>\n",
       "      <th>action_type_Running Bank shot</th>\n",
       "      <th>action_type_Running Dunk Shot</th>\n",
       "      <th>action_type_Running Hook Shot</th>\n",
       "      <th>action_type_Running Jump Shot</th>\n",
       "      <th>action_type_Running Layup Shot</th>\n",
       "      <th>action_type_Slam Dunk Shot</th>\n",
       "      <th>action_type_Step Back Jump shot</th>\n",
       "      <th>action_type_Tip Shot</th>\n",
       "      <th>action_type_Turnaround Bank shot</th>\n",
       "      <th>action_type_Turnaround Fadeaway shot</th>\n",
       "      <th>action_type_Turnaround Jump Shot</th>\n",
       "      <th>combined_shot_type_Bank Shot</th>\n",
       "      <th>combined_shot_type_Dunk</th>\n",
       "      <th>combined_shot_type_Hook Shot</th>\n",
       "      <th>combined_shot_type_Jump Shot</th>\n",
       "      <th>combined_shot_type_Layup</th>\n",
       "      <th>combined_shot_type_Tip Shot</th>\n",
       "      <th>period_1</th>\n",
       "      <th>period_2</th>\n",
       "      <th>period_3</th>\n",
       "      <th>period_4</th>\n",
       "      <th>period_5</th>\n",
       "      <th>period_6</th>\n",
       "      <th>period_7</th>\n",
       "      <th>season_1996-97</th>\n",
       "      <th>season_1997-98</th>\n",
       "      <th>season_1998-99</th>\n",
       "      <th>season_1999-00</th>\n",
       "      <th>season_2000-01</th>\n",
       "      <th>season_2001-02</th>\n",
       "      <th>season_2002-03</th>\n",
       "      <th>season_2003-04</th>\n",
       "      <th>season_2004-05</th>\n",
       "      <th>season_2005-06</th>\n",
       "      <th>season_2006-07</th>\n",
       "      <th>season_2007-08</th>\n",
       "      <th>season_2008-09</th>\n",
       "      <th>season_2009-10</th>\n",
       "      <th>season_2010-11</th>\n",
       "      <th>season_2011-12</th>\n",
       "      <th>season_2012-13</th>\n",
       "      <th>season_2013-14</th>\n",
       "      <th>season_2014-15</th>\n",
       "      <th>season_2015-16</th>\n",
       "      <th>shot_type_2PT Field Goal</th>\n",
       "      <th>shot_type_3PT Field Goal</th>\n",
       "      <th>shot_zone_area_Back Court(BC)</th>\n",
       "      <th>shot_zone_area_Center(C)</th>\n",
       "      <th>shot_zone_area_Left Side Center(LC)</th>\n",
       "      <th>shot_zone_area_Left Side(L)</th>\n",
       "      <th>shot_zone_area_Right Side Center(RC)</th>\n",
       "      <th>shot_zone_area_Right Side(R)</th>\n",
       "      <th>shot_zone_basic_Above the Break 3</th>\n",
       "      <th>shot_zone_basic_Backcourt</th>\n",
       "      <th>shot_zone_basic_In The Paint (Non-RA)</th>\n",
       "      <th>shot_zone_basic_Left Corner 3</th>\n",
       "      <th>shot_zone_basic_Mid-Range</th>\n",
       "      <th>shot_zone_basic_Restricted Area</th>\n",
       "      <th>shot_zone_basic_Right Corner 3</th>\n",
       "      <th>shot_zone_range_16-24 ft.</th>\n",
       "      <th>shot_zone_range_24+ ft.</th>\n",
       "      <th>shot_zone_range_8-16 ft.</th>\n",
       "      <th>shot_zone_range_Back Court Shot</th>\n",
       "      <th>shot_zone_range_Less Than 8 ft.</th>\n",
       "      <th>game_year_1996</th>\n",
       "      <th>game_year_1997</th>\n",
       "      <th>game_year_1998</th>\n",
       "      <th>game_year_1999</th>\n",
       "      <th>game_year_2000</th>\n",
       "      <th>game_year_2001</th>\n",
       "      <th>game_year_2002</th>\n",
       "      <th>game_year_2003</th>\n",
       "      <th>game_year_2004</th>\n",
       "      <th>game_year_2005</th>\n",
       "      <th>game_year_2006</th>\n",
       "      <th>game_year_2007</th>\n",
       "      <th>game_year_2008</th>\n",
       "      <th>game_year_2009</th>\n",
       "      <th>game_year_2010</th>\n",
       "      <th>game_year_2011</th>\n",
       "      <th>game_year_2012</th>\n",
       "      <th>game_year_2013</th>\n",
       "      <th>game_year_2014</th>\n",
       "      <th>game_year_2015</th>\n",
       "      <th>game_year_2016</th>\n",
       "      <th>game_month_1</th>\n",
       "      <th>game_month_2</th>\n",
       "      <th>game_month_3</th>\n",
       "      <th>game_month_4</th>\n",
       "      <th>game_month_5</th>\n",
       "      <th>game_month_6</th>\n",
       "      <th>game_month_10</th>\n",
       "      <th>game_month_11</th>\n",
       "      <th>game_month_12</th>\n",
       "      <th>opponent_ATL</th>\n",
       "      <th>opponent_BKN</th>\n",
       "      <th>opponent_BOS</th>\n",
       "      <th>opponent_CHA</th>\n",
       "      <th>opponent_CHI</th>\n",
       "      <th>opponent_CLE</th>\n",
       "      <th>opponent_DAL</th>\n",
       "      <th>opponent_DEN</th>\n",
       "      <th>opponent_DET</th>\n",
       "      <th>opponent_GSW</th>\n",
       "      <th>opponent_HOU</th>\n",
       "      <th>opponent_IND</th>\n",
       "      <th>opponent_LAC</th>\n",
       "      <th>opponent_MEM</th>\n",
       "      <th>opponent_MIA</th>\n",
       "      <th>opponent_MIL</th>\n",
       "      <th>opponent_MIN</th>\n",
       "      <th>opponent_NJN</th>\n",
       "      <th>opponent_NOH</th>\n",
       "      <th>opponent_NOP</th>\n",
       "      <th>opponent_NYK</th>\n",
       "      <th>opponent_OKC</th>\n",
       "      <th>opponent_ORL</th>\n",
       "      <th>opponent_PHI</th>\n",
       "      <th>opponent_PHX</th>\n",
       "      <th>opponent_POR</th>\n",
       "      <th>opponent_SAC</th>\n",
       "      <th>opponent_SAS</th>\n",
       "      <th>opponent_SEA</th>\n",
       "      <th>opponent_TOR</th>\n",
       "      <th>opponent_UTA</th>\n",
       "      <th>opponent_VAN</th>\n",
       "      <th>opponent_WAS</th>\n",
       "      <th>loc_x_(-250.498, -230.08]</th>\n",
       "      <th>loc_x_(-230.08, -210.16]</th>\n",
       "      <th>loc_x_(-210.16, -190.24]</th>\n",
       "      <th>loc_x_(-190.24, -170.32]</th>\n",
       "      <th>loc_x_(-170.32, -150.4]</th>\n",
       "      <th>loc_x_(-150.4, -130.48]</th>\n",
       "      <th>loc_x_(-130.48, -110.56]</th>\n",
       "      <th>loc_x_(-110.56, -90.64]</th>\n",
       "      <th>loc_x_(-90.64, -70.72]</th>\n",
       "      <th>loc_x_(-70.72, -50.8]</th>\n",
       "      <th>loc_x_(-50.8, -30.88]</th>\n",
       "      <th>loc_x_(-30.88, -10.96]</th>\n",
       "      <th>loc_x_(-10.96, 8.96]</th>\n",
       "      <th>loc_x_(8.96, 28.88]</th>\n",
       "      <th>loc_x_(28.88, 48.8]</th>\n",
       "      <th>loc_x_(48.8, 68.72]</th>\n",
       "      <th>loc_x_(68.72, 88.64]</th>\n",
       "      <th>loc_x_(88.64, 108.56]</th>\n",
       "      <th>loc_x_(108.56, 128.48]</th>\n",
       "      <th>loc_x_(128.48, 148.4]</th>\n",
       "      <th>loc_x_(148.4, 168.32]</th>\n",
       "      <th>loc_x_(168.32, 188.24]</th>\n",
       "      <th>loc_x_(188.24, 208.16]</th>\n",
       "      <th>loc_x_(208.16, 228.08]</th>\n",
       "      <th>loc_x_(228.08, 248.0]</th>\n",
       "      <th>loc_y_(-44.835, -10.6]</th>\n",
       "      <th>loc_y_(-10.6, 22.8]</th>\n",
       "      <th>loc_y_(22.8, 56.2]</th>\n",
       "      <th>loc_y_(56.2, 89.6]</th>\n",
       "      <th>loc_y_(89.6, 123.0]</th>\n",
       "      <th>loc_y_(123.0, 156.4]</th>\n",
       "      <th>loc_y_(156.4, 189.8]</th>\n",
       "      <th>loc_y_(189.8, 223.2]</th>\n",
       "      <th>loc_y_(223.2, 256.6]</th>\n",
       "      <th>loc_y_(256.6, 290.0]</th>\n",
       "      <th>loc_y_(290.0, 323.4]</th>\n",
       "      <th>loc_y_(323.4, 356.8]</th>\n",
       "      <th>loc_y_(356.8, 390.2]</th>\n",
       "      <th>loc_y_(390.2, 423.6]</th>\n",
       "      <th>loc_y_(423.6, 457.0]</th>\n",
       "      <th>loc_y_(457.0, 490.4]</th>\n",
       "      <th>loc_y_(490.4, 523.8]</th>\n",
       "      <th>loc_y_(523.8, 557.2]</th>\n",
       "      <th>loc_y_(557.2, 590.6]</th>\n",
       "      <th>loc_y_(590.6, 624.0]</th>\n",
       "      <th>loc_y_(624.0, 657.4]</th>\n",
       "      <th>loc_y_(657.4, 690.8]</th>\n",
       "      <th>loc_y_(690.8, 724.2]</th>\n",
       "      <th>loc_y_(724.2, 757.6]</th>\n",
       "      <th>loc_y_(757.6, 791.0]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>40.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.093053</td>\n",
       "      <td>-0.000727</td>\n",
       "      <td>-0.712689</td>\n",
       "      <td>0.048389</td>\n",
       "      <td>0.245134</td>\n",
       "      <td>-0.024445</td>\n",
       "      <td>0.899716</td>\n",
       "      <td>0.783623</td>\n",
       "      <td>0.636809</td>\n",
       "      <td>-0.574973</td>\n",
       "      <td>0.155241</td>\n",
       "      <td>0.269374</td>\n",
       "      <td>0.522294</td>\n",
       "      <td>-1.052781</td>\n",
       "      <td>0.879697</td>\n",
       "      <td>-0.391270</td>\n",
       "      <td>0.415424</td>\n",
       "      <td>-0.687313</td>\n",
       "      <td>0.289430</td>\n",
       "      <td>-0.046363</td>\n",
       "      <td>-1.074137</td>\n",
       "      <td>0.592894</td>\n",
       "      <td>0.251523</td>\n",
       "      <td>-1.549020</td>\n",
       "      <td>-1.349372</td>\n",
       "      <td>-0.335740</td>\n",
       "      <td>0.284715</td>\n",
       "      <td>-0.082439</td>\n",
       "      <td>-0.056372</td>\n",
       "      <td>-0.347727</td>\n",
       "      <td>0.400066</td>\n",
       "      <td>0.323066</td>\n",
       "      <td>-0.116988</td>\n",
       "      <td>0.759172</td>\n",
       "      <td>0.372647</td>\n",
       "      <td>0.036409</td>\n",
       "      <td>1.084993</td>\n",
       "      <td>-0.134388</td>\n",
       "      <td>-0.690061</td>\n",
       "      <td>0.109589</td>\n",
       "      <td>-0.252588</td>\n",
       "      <td>-0.334093</td>\n",
       "      <td>0.365711</td>\n",
       "      <td>1.291626</td>\n",
       "      <td>-0.113032</td>\n",
       "      <td>-0.242881</td>\n",
       "      <td>-0.183500</td>\n",
       "      <td>-0.906175</td>\n",
       "      <td>0.155511</td>\n",
       "      <td>0.101724</td>\n",
       "      <td>0.085157</td>\n",
       "      <td>-0.048844</td>\n",
       "      <td>-0.007572</td>\n",
       "      <td>-0.004387</td>\n",
       "      <td>-0.069840</td>\n",
       "      <td>0.051563</td>\n",
       "      <td>-0.093281</td>\n",
       "      <td>0.096971</td>\n",
       "      <td>0.018851</td>\n",
       "      <td>0.113854</td>\n",
       "      <td>0.185078</td>\n",
       "      <td>0.161640</td>\n",
       "      <td>0.020736</td>\n",
       "      <td>-0.087354</td>\n",
       "      <td>-0.054919</td>\n",
       "      <td>0.012259</td>\n",
       "      <td>0.012480</td>\n",
       "      <td>0.040967</td>\n",
       "      <td>0.011077</td>\n",
       "      <td>0.009685</td>\n",
       "      <td>-0.010631</td>\n",
       "      <td>0.085257</td>\n",
       "      <td>0.059069</td>\n",
       "      <td>-0.120369</td>\n",
       "      <td>-0.301187</td>\n",
       "      <td>0.045509</td>\n",
       "      <td>0.166240</td>\n",
       "      <td>-0.539157</td>\n",
       "      <td>0.180677</td>\n",
       "      <td>0.017662</td>\n",
       "      <td>-0.006811</td>\n",
       "      <td>0.298203</td>\n",
       "      <td>0.261174</td>\n",
       "      <td>-0.245895</td>\n",
       "      <td>-0.385099</td>\n",
       "      <td>0.138121</td>\n",
       "      <td>0.346058</td>\n",
       "      <td>0.059446</td>\n",
       "      <td>0.297299</td>\n",
       "      <td>0.001818</td>\n",
       "      <td>0.244209</td>\n",
       "      <td>0.256039</td>\n",
       "      <td>0.228884</td>\n",
       "      <td>-0.539157</td>\n",
       "      <td>0.021774</td>\n",
       "      <td>-0.065477</td>\n",
       "      <td>0.004729</td>\n",
       "      <td>0.019030</td>\n",
       "      <td>0.097155</td>\n",
       "      <td>0.150650</td>\n",
       "      <td>-0.008947</td>\n",
       "      <td>-0.126750</td>\n",
       "      <td>-0.071629</td>\n",
       "      <td>0.001050</td>\n",
       "      <td>0.229996</td>\n",
       "      <td>0.275859</td>\n",
       "      <td>0.112411</td>\n",
       "      <td>0.096170</td>\n",
       "      <td>0.082606</td>\n",
       "      <td>0.018712</td>\n",
       "      <td>0.002069</td>\n",
       "      <td>-0.024652</td>\n",
       "      <td>-0.159678</td>\n",
       "      <td>-0.134910</td>\n",
       "      <td>-0.081101</td>\n",
       "      <td>-0.205545</td>\n",
       "      <td>0.070159</td>\n",
       "      <td>0.041372</td>\n",
       "      <td>-0.040715</td>\n",
       "      <td>-0.025546</td>\n",
       "      <td>0.156930</td>\n",
       "      <td>0.022647</td>\n",
       "      <td>-0.018554</td>\n",
       "      <td>0.005149</td>\n",
       "      <td>0.000306</td>\n",
       "      <td>-0.018743</td>\n",
       "      <td>-0.344178</td>\n",
       "      <td>-0.039958</td>\n",
       "      <td>0.046997</td>\n",
       "      <td>0.051972</td>\n",
       "      <td>-0.013875</td>\n",
       "      <td>0.029760</td>\n",
       "      <td>0.031328</td>\n",
       "      <td>0.063125</td>\n",
       "      <td>-0.056893</td>\n",
       "      <td>-0.108757</td>\n",
       "      <td>-0.074839</td>\n",
       "      <td>0.010762</td>\n",
       "      <td>-0.018047</td>\n",
       "      <td>-0.053903</td>\n",
       "      <td>0.058901</td>\n",
       "      <td>0.030095</td>\n",
       "      <td>-0.164618</td>\n",
       "      <td>0.113523</td>\n",
       "      <td>0.056353</td>\n",
       "      <td>0.221332</td>\n",
       "      <td>-0.153844</td>\n",
       "      <td>-0.039589</td>\n",
       "      <td>0.033365</td>\n",
       "      <td>0.139102</td>\n",
       "      <td>0.048882</td>\n",
       "      <td>0.144058</td>\n",
       "      <td>0.009122</td>\n",
       "      <td>0.079894</td>\n",
       "      <td>-0.109594</td>\n",
       "      <td>0.043009</td>\n",
       "      <td>0.137749</td>\n",
       "      <td>0.059258</td>\n",
       "      <td>0.000948</td>\n",
       "      <td>0.206578</td>\n",
       "      <td>0.211461</td>\n",
       "      <td>0.163798</td>\n",
       "      <td>0.175974</td>\n",
       "      <td>0.101195</td>\n",
       "      <td>-0.068512</td>\n",
       "      <td>0.007018</td>\n",
       "      <td>0.056858</td>\n",
       "      <td>-0.078517</td>\n",
       "      <td>-0.111587</td>\n",
       "      <td>-0.013268</td>\n",
       "      <td>0.057450</td>\n",
       "      <td>0.048331</td>\n",
       "      <td>-0.013171</td>\n",
       "      <td>-0.001099</td>\n",
       "      <td>-0.096437</td>\n",
       "      <td>-0.213162</td>\n",
       "      <td>-0.098075</td>\n",
       "      <td>-0.185397</td>\n",
       "      <td>-0.110042</td>\n",
       "      <td>0.064878</td>\n",
       "      <td>0.074967</td>\n",
       "      <td>-0.095597</td>\n",
       "      <td>0.127157</td>\n",
       "      <td>0.034805</td>\n",
       "      <td>0.096461</td>\n",
       "      <td>-0.006612</td>\n",
       "      <td>0.076793</td>\n",
       "      <td>0.186131</td>\n",
       "      <td>0.430928</td>\n",
       "      <td>0.417530</td>\n",
       "      <td>0.378376</td>\n",
       "      <td>0.387631</td>\n",
       "      <td>0.254683</td>\n",
       "      <td>-0.369742</td>\n",
       "      <td>0.008790</td>\n",
       "      <td>-0.792352</td>\n",
       "      <td>-0.506574</td>\n",
       "      <td>0.278369</td>\n",
       "      <td>-0.088160</td>\n",
       "      <td>-0.140745</td>\n",
       "      <td>-0.054666</td>\n",
       "      <td>-0.114648</td>\n",
       "      <td>-0.075653</td>\n",
       "      <td>-0.058603</td>\n",
       "      <td>-0.032135</td>\n",
       "      <td>-0.045107</td>\n",
       "      <td>-0.031875</td>\n",
       "      <td>-0.021876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.018136</td>\n",
       "      <td>0.003649</td>\n",
       "      <td>0.101160</td>\n",
       "      <td>0.001487</td>\n",
       "      <td>0.045950</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.198034</td>\n",
       "      <td>0.205713</td>\n",
       "      <td>0.151185</td>\n",
       "      <td>0.197234</td>\n",
       "      <td>0.044420</td>\n",
       "      <td>0.048643</td>\n",
       "      <td>0.193077</td>\n",
       "      <td>0.263196</td>\n",
       "      <td>0.285817</td>\n",
       "      <td>0.093184</td>\n",
       "      <td>0.122196</td>\n",
       "      <td>0.226901</td>\n",
       "      <td>0.051386</td>\n",
       "      <td>0.033601</td>\n",
       "      <td>0.292607</td>\n",
       "      <td>0.088484</td>\n",
       "      <td>0.074990</td>\n",
       "      <td>0.174891</td>\n",
       "      <td>0.180457</td>\n",
       "      <td>0.109667</td>\n",
       "      <td>0.044644</td>\n",
       "      <td>0.043688</td>\n",
       "      <td>0.050554</td>\n",
       "      <td>0.085624</td>\n",
       "      <td>0.183174</td>\n",
       "      <td>0.074092</td>\n",
       "      <td>0.068937</td>\n",
       "      <td>0.216152</td>\n",
       "      <td>0.049740</td>\n",
       "      <td>0.018790</td>\n",
       "      <td>0.236456</td>\n",
       "      <td>0.060634</td>\n",
       "      <td>0.114408</td>\n",
       "      <td>0.022559</td>\n",
       "      <td>0.073044</td>\n",
       "      <td>0.087009</td>\n",
       "      <td>0.059987</td>\n",
       "      <td>0.182201</td>\n",
       "      <td>0.046063</td>\n",
       "      <td>0.035430</td>\n",
       "      <td>0.018572</td>\n",
       "      <td>0.188227</td>\n",
       "      <td>0.015474</td>\n",
       "      <td>0.012965</td>\n",
       "      <td>0.009044</td>\n",
       "      <td>0.003392</td>\n",
       "      <td>0.004496</td>\n",
       "      <td>0.005891</td>\n",
       "      <td>0.031096</td>\n",
       "      <td>0.010435</td>\n",
       "      <td>0.015414</td>\n",
       "      <td>0.014681</td>\n",
       "      <td>0.006959</td>\n",
       "      <td>0.018909</td>\n",
       "      <td>0.036185</td>\n",
       "      <td>0.031453</td>\n",
       "      <td>0.006664</td>\n",
       "      <td>0.026247</td>\n",
       "      <td>0.033650</td>\n",
       "      <td>0.023476</td>\n",
       "      <td>0.021789</td>\n",
       "      <td>0.016627</td>\n",
       "      <td>0.009775</td>\n",
       "      <td>0.005467</td>\n",
       "      <td>0.014950</td>\n",
       "      <td>0.021557</td>\n",
       "      <td>0.026225</td>\n",
       "      <td>0.017243</td>\n",
       "      <td>0.043101</td>\n",
       "      <td>0.041318</td>\n",
       "      <td>0.028663</td>\n",
       "      <td>0.160596</td>\n",
       "      <td>0.027222</td>\n",
       "      <td>0.006668</td>\n",
       "      <td>0.006507</td>\n",
       "      <td>0.058680</td>\n",
       "      <td>0.064817</td>\n",
       "      <td>0.055024</td>\n",
       "      <td>0.108744</td>\n",
       "      <td>0.039124</td>\n",
       "      <td>0.064949</td>\n",
       "      <td>0.019599</td>\n",
       "      <td>0.051913</td>\n",
       "      <td>0.029698</td>\n",
       "      <td>0.037442</td>\n",
       "      <td>0.040914</td>\n",
       "      <td>0.048028</td>\n",
       "      <td>0.160596</td>\n",
       "      <td>0.036059</td>\n",
       "      <td>0.020551</td>\n",
       "      <td>0.002586</td>\n",
       "      <td>0.008909</td>\n",
       "      <td>0.015141</td>\n",
       "      <td>0.020860</td>\n",
       "      <td>0.015009</td>\n",
       "      <td>0.028162</td>\n",
       "      <td>0.019716</td>\n",
       "      <td>0.004349</td>\n",
       "      <td>0.045186</td>\n",
       "      <td>0.047079</td>\n",
       "      <td>0.025115</td>\n",
       "      <td>0.016706</td>\n",
       "      <td>0.013080</td>\n",
       "      <td>0.003876</td>\n",
       "      <td>0.004744</td>\n",
       "      <td>0.022190</td>\n",
       "      <td>0.037722</td>\n",
       "      <td>0.020683</td>\n",
       "      <td>0.009713</td>\n",
       "      <td>0.030542</td>\n",
       "      <td>0.008402</td>\n",
       "      <td>0.006438</td>\n",
       "      <td>0.010232</td>\n",
       "      <td>0.005964</td>\n",
       "      <td>0.022060</td>\n",
       "      <td>0.007123</td>\n",
       "      <td>0.006214</td>\n",
       "      <td>0.006273</td>\n",
       "      <td>0.007942</td>\n",
       "      <td>0.003287</td>\n",
       "      <td>0.102250</td>\n",
       "      <td>0.004584</td>\n",
       "      <td>0.008847</td>\n",
       "      <td>0.010361</td>\n",
       "      <td>0.002111</td>\n",
       "      <td>0.003608</td>\n",
       "      <td>0.002946</td>\n",
       "      <td>0.011183</td>\n",
       "      <td>0.010889</td>\n",
       "      <td>0.015435</td>\n",
       "      <td>0.010126</td>\n",
       "      <td>0.000903</td>\n",
       "      <td>0.002662</td>\n",
       "      <td>0.009065</td>\n",
       "      <td>0.014015</td>\n",
       "      <td>0.003716</td>\n",
       "      <td>0.027765</td>\n",
       "      <td>0.019086</td>\n",
       "      <td>0.012906</td>\n",
       "      <td>0.034533</td>\n",
       "      <td>0.023708</td>\n",
       "      <td>0.005892</td>\n",
       "      <td>0.004660</td>\n",
       "      <td>0.018039</td>\n",
       "      <td>0.004664</td>\n",
       "      <td>0.020066</td>\n",
       "      <td>0.002829</td>\n",
       "      <td>0.011262</td>\n",
       "      <td>0.019087</td>\n",
       "      <td>0.006371</td>\n",
       "      <td>0.028164</td>\n",
       "      <td>0.010289</td>\n",
       "      <td>0.015999</td>\n",
       "      <td>0.042190</td>\n",
       "      <td>0.049450</td>\n",
       "      <td>0.041436</td>\n",
       "      <td>0.040811</td>\n",
       "      <td>0.030844</td>\n",
       "      <td>0.020649</td>\n",
       "      <td>0.021834</td>\n",
       "      <td>0.019085</td>\n",
       "      <td>0.012450</td>\n",
       "      <td>0.018233</td>\n",
       "      <td>0.007026</td>\n",
       "      <td>0.011526</td>\n",
       "      <td>0.009050</td>\n",
       "      <td>0.006851</td>\n",
       "      <td>0.012877</td>\n",
       "      <td>0.033303</td>\n",
       "      <td>0.043414</td>\n",
       "      <td>0.031848</td>\n",
       "      <td>0.038640</td>\n",
       "      <td>0.029593</td>\n",
       "      <td>0.020898</td>\n",
       "      <td>0.022350</td>\n",
       "      <td>0.027549</td>\n",
       "      <td>0.024269</td>\n",
       "      <td>0.058746</td>\n",
       "      <td>0.061976</td>\n",
       "      <td>0.059888</td>\n",
       "      <td>0.062626</td>\n",
       "      <td>0.069598</td>\n",
       "      <td>0.089287</td>\n",
       "      <td>0.090242</td>\n",
       "      <td>0.090397</td>\n",
       "      <td>0.098488</td>\n",
       "      <td>0.085418</td>\n",
       "      <td>0.105487</td>\n",
       "      <td>0.012109</td>\n",
       "      <td>0.343188</td>\n",
       "      <td>0.219614</td>\n",
       "      <td>0.168393</td>\n",
       "      <td>0.034311</td>\n",
       "      <td>0.057512</td>\n",
       "      <td>0.022294</td>\n",
       "      <td>0.045850</td>\n",
       "      <td>0.030421</td>\n",
       "      <td>0.024434</td>\n",
       "      <td>0.013764</td>\n",
       "      <td>0.019109</td>\n",
       "      <td>0.013882</td>\n",
       "      <td>0.009686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.101460</td>\n",
       "      <td>-0.013534</td>\n",
       "      <td>-0.736455</td>\n",
       "      <td>0.045628</td>\n",
       "      <td>0.024030</td>\n",
       "      <td>-0.064598</td>\n",
       "      <td>0.070274</td>\n",
       "      <td>0.015647</td>\n",
       "      <td>0.016555</td>\n",
       "      <td>-0.781493</td>\n",
       "      <td>0.109979</td>\n",
       "      <td>0.012166</td>\n",
       "      <td>0.012264</td>\n",
       "      <td>-1.226231</td>\n",
       "      <td>0.010025</td>\n",
       "      <td>-0.466938</td>\n",
       "      <td>0.006243</td>\n",
       "      <td>-0.906866</td>\n",
       "      <td>0.016589</td>\n",
       "      <td>-0.093926</td>\n",
       "      <td>-1.338320</td>\n",
       "      <td>0.071413</td>\n",
       "      <td>0.003492</td>\n",
       "      <td>-1.640757</td>\n",
       "      <td>-1.432840</td>\n",
       "      <td>-0.440416</td>\n",
       "      <td>0.083998</td>\n",
       "      <td>-0.140310</td>\n",
       "      <td>-0.105802</td>\n",
       "      <td>-0.414669</td>\n",
       "      <td>0.004771</td>\n",
       "      <td>0.012466</td>\n",
       "      <td>-0.205913</td>\n",
       "      <td>0.010456</td>\n",
       "      <td>0.145004</td>\n",
       "      <td>0.005345</td>\n",
       "      <td>0.091378</td>\n",
       "      <td>-0.204374</td>\n",
       "      <td>-0.740734</td>\n",
       "      <td>0.014449</td>\n",
       "      <td>-0.323097</td>\n",
       "      <td>-0.407454</td>\n",
       "      <td>0.029669</td>\n",
       "      <td>0.241725</td>\n",
       "      <td>-0.192241</td>\n",
       "      <td>-0.259842</td>\n",
       "      <td>-0.199945</td>\n",
       "      <td>-1.076019</td>\n",
       "      <td>0.062283</td>\n",
       "      <td>0.024470</td>\n",
       "      <td>0.032232</td>\n",
       "      <td>-0.054773</td>\n",
       "      <td>-0.015199</td>\n",
       "      <td>-0.013682</td>\n",
       "      <td>-0.109885</td>\n",
       "      <td>-0.005850</td>\n",
       "      <td>-0.104881</td>\n",
       "      <td>0.010274</td>\n",
       "      <td>0.003793</td>\n",
       "      <td>0.019121</td>\n",
       "      <td>0.006977</td>\n",
       "      <td>0.004504</td>\n",
       "      <td>-0.014680</td>\n",
       "      <td>-0.110035</td>\n",
       "      <td>-0.085255</td>\n",
       "      <td>-0.011810</td>\n",
       "      <td>-0.011245</td>\n",
       "      <td>0.022387</td>\n",
       "      <td>-0.001433</td>\n",
       "      <td>0.001257</td>\n",
       "      <td>-0.047676</td>\n",
       "      <td>0.012124</td>\n",
       "      <td>-0.003103</td>\n",
       "      <td>-0.131513</td>\n",
       "      <td>-0.316590</td>\n",
       "      <td>-0.009880</td>\n",
       "      <td>0.005783</td>\n",
       "      <td>-0.711816</td>\n",
       "      <td>0.061448</td>\n",
       "      <td>0.011437</td>\n",
       "      <td>-0.020853</td>\n",
       "      <td>0.052727</td>\n",
       "      <td>-0.010554</td>\n",
       "      <td>-0.286435</td>\n",
       "      <td>-0.499688</td>\n",
       "      <td>-0.015579</td>\n",
       "      <td>0.011332</td>\n",
       "      <td>0.002260</td>\n",
       "      <td>0.090432</td>\n",
       "      <td>-0.036372</td>\n",
       "      <td>0.041882</td>\n",
       "      <td>0.015708</td>\n",
       "      <td>0.016023</td>\n",
       "      <td>-0.711816</td>\n",
       "      <td>-0.071123</td>\n",
       "      <td>-0.085429</td>\n",
       "      <td>-0.009142</td>\n",
       "      <td>-0.012011</td>\n",
       "      <td>0.010792</td>\n",
       "      <td>0.032615</td>\n",
       "      <td>-0.024976</td>\n",
       "      <td>-0.148460</td>\n",
       "      <td>-0.087833</td>\n",
       "      <td>-0.013708</td>\n",
       "      <td>0.010525</td>\n",
       "      <td>0.044983</td>\n",
       "      <td>0.017474</td>\n",
       "      <td>0.031801</td>\n",
       "      <td>0.026251</td>\n",
       "      <td>0.002620</td>\n",
       "      <td>-0.004150</td>\n",
       "      <td>-0.049371</td>\n",
       "      <td>-0.192723</td>\n",
       "      <td>-0.146090</td>\n",
       "      <td>-0.085584</td>\n",
       "      <td>-0.217943</td>\n",
       "      <td>0.031968</td>\n",
       "      <td>0.030474</td>\n",
       "      <td>-0.052270</td>\n",
       "      <td>-0.034281</td>\n",
       "      <td>0.026707</td>\n",
       "      <td>-0.009276</td>\n",
       "      <td>-0.028006</td>\n",
       "      <td>-0.003830</td>\n",
       "      <td>-0.010174</td>\n",
       "      <td>-0.022612</td>\n",
       "      <td>-0.434772</td>\n",
       "      <td>-0.041504</td>\n",
       "      <td>0.001895</td>\n",
       "      <td>-0.000746</td>\n",
       "      <td>-0.017513</td>\n",
       "      <td>0.007971</td>\n",
       "      <td>0.013580</td>\n",
       "      <td>0.001709</td>\n",
       "      <td>-0.062018</td>\n",
       "      <td>-0.112340</td>\n",
       "      <td>-0.080212</td>\n",
       "      <td>0.008113</td>\n",
       "      <td>-0.019875</td>\n",
       "      <td>-0.059187</td>\n",
       "      <td>-0.008700</td>\n",
       "      <td>0.007545</td>\n",
       "      <td>-0.176977</td>\n",
       "      <td>0.006654</td>\n",
       "      <td>-0.002009</td>\n",
       "      <td>0.020976</td>\n",
       "      <td>-0.163294</td>\n",
       "      <td>-0.042428</td>\n",
       "      <td>0.005174</td>\n",
       "      <td>0.031757</td>\n",
       "      <td>0.020361</td>\n",
       "      <td>0.024663</td>\n",
       "      <td>-0.005870</td>\n",
       "      <td>0.011383</td>\n",
       "      <td>-0.117698</td>\n",
       "      <td>0.005427</td>\n",
       "      <td>0.003223</td>\n",
       "      <td>0.001633</td>\n",
       "      <td>-0.027085</td>\n",
       "      <td>0.005763</td>\n",
       "      <td>0.002493</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>0.006281</td>\n",
       "      <td>-0.002246</td>\n",
       "      <td>-0.115374</td>\n",
       "      <td>-0.041307</td>\n",
       "      <td>0.008135</td>\n",
       "      <td>-0.088423</td>\n",
       "      <td>-0.120745</td>\n",
       "      <td>-0.019938</td>\n",
       "      <td>0.047884</td>\n",
       "      <td>0.001631</td>\n",
       "      <td>-0.020004</td>\n",
       "      <td>-0.011395</td>\n",
       "      <td>-0.119683</td>\n",
       "      <td>-0.239324</td>\n",
       "      <td>-0.123433</td>\n",
       "      <td>-0.216598</td>\n",
       "      <td>-0.141002</td>\n",
       "      <td>0.015912</td>\n",
       "      <td>0.009696</td>\n",
       "      <td>-0.137059</td>\n",
       "      <td>0.007138</td>\n",
       "      <td>-0.055769</td>\n",
       "      <td>-0.002447</td>\n",
       "      <td>-0.102745</td>\n",
       "      <td>-0.027164</td>\n",
       "      <td>0.006561</td>\n",
       "      <td>0.070188</td>\n",
       "      <td>0.053200</td>\n",
       "      <td>0.017181</td>\n",
       "      <td>-0.003534</td>\n",
       "      <td>-0.011955</td>\n",
       "      <td>-0.464588</td>\n",
       "      <td>-0.020474</td>\n",
       "      <td>-1.244814</td>\n",
       "      <td>-0.814492</td>\n",
       "      <td>-0.000535</td>\n",
       "      <td>-0.136724</td>\n",
       "      <td>-0.223031</td>\n",
       "      <td>-0.087991</td>\n",
       "      <td>-0.182277</td>\n",
       "      <td>-0.121722</td>\n",
       "      <td>-0.096671</td>\n",
       "      <td>-0.054143</td>\n",
       "      <td>-0.076084</td>\n",
       "      <td>-0.054854</td>\n",
       "      <td>-0.038340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.100388</td>\n",
       "      <td>-0.003436</td>\n",
       "      <td>-0.736014</td>\n",
       "      <td>0.047571</td>\n",
       "      <td>0.241579</td>\n",
       "      <td>-0.051271</td>\n",
       "      <td>0.856513</td>\n",
       "      <td>0.737975</td>\n",
       "      <td>0.619739</td>\n",
       "      <td>-0.722235</td>\n",
       "      <td>0.125620</td>\n",
       "      <td>0.278531</td>\n",
       "      <td>0.408558</td>\n",
       "      <td>-1.202162</td>\n",
       "      <td>0.763475</td>\n",
       "      <td>-0.445905</td>\n",
       "      <td>0.377956</td>\n",
       "      <td>-0.848998</td>\n",
       "      <td>0.294627</td>\n",
       "      <td>-0.076487</td>\n",
       "      <td>-1.268141</td>\n",
       "      <td>0.598310</td>\n",
       "      <td>0.231887</td>\n",
       "      <td>-1.619009</td>\n",
       "      <td>-1.416126</td>\n",
       "      <td>-0.416060</td>\n",
       "      <td>0.262292</td>\n",
       "      <td>-0.120786</td>\n",
       "      <td>-0.095928</td>\n",
       "      <td>-0.396533</td>\n",
       "      <td>0.269718</td>\n",
       "      <td>0.314604</td>\n",
       "      <td>-0.174804</td>\n",
       "      <td>0.704857</td>\n",
       "      <td>0.349169</td>\n",
       "      <td>0.021097</td>\n",
       "      <td>1.032390</td>\n",
       "      <td>-0.181794</td>\n",
       "      <td>-0.732697</td>\n",
       "      <td>0.097057</td>\n",
       "      <td>-0.302313</td>\n",
       "      <td>-0.386184</td>\n",
       "      <td>0.379280</td>\n",
       "      <td>1.327187</td>\n",
       "      <td>-0.148950</td>\n",
       "      <td>-0.258476</td>\n",
       "      <td>-0.193834</td>\n",
       "      <td>-1.020281</td>\n",
       "      <td>0.156321</td>\n",
       "      <td>0.101999</td>\n",
       "      <td>0.084409</td>\n",
       "      <td>-0.051611</td>\n",
       "      <td>-0.011199</td>\n",
       "      <td>-0.009677</td>\n",
       "      <td>-0.096453</td>\n",
       "      <td>0.049071</td>\n",
       "      <td>-0.101926</td>\n",
       "      <td>0.096177</td>\n",
       "      <td>0.014333</td>\n",
       "      <td>0.112363</td>\n",
       "      <td>0.185702</td>\n",
       "      <td>0.163806</td>\n",
       "      <td>0.019724</td>\n",
       "      <td>-0.105474</td>\n",
       "      <td>-0.079247</td>\n",
       "      <td>-0.006547</td>\n",
       "      <td>-0.005639</td>\n",
       "      <td>0.027346</td>\n",
       "      <td>0.002995</td>\n",
       "      <td>0.004779</td>\n",
       "      <td>-0.017599</td>\n",
       "      <td>0.077543</td>\n",
       "      <td>0.045723</td>\n",
       "      <td>-0.128036</td>\n",
       "      <td>-0.314188</td>\n",
       "      <td>0.009287</td>\n",
       "      <td>0.163842</td>\n",
       "      <td>-0.661271</td>\n",
       "      <td>0.175521</td>\n",
       "      <td>0.013254</td>\n",
       "      <td>-0.011018</td>\n",
       "      <td>0.285053</td>\n",
       "      <td>0.249505</td>\n",
       "      <td>-0.277639</td>\n",
       "      <td>-0.464433</td>\n",
       "      <td>0.129136</td>\n",
       "      <td>0.358730</td>\n",
       "      <td>0.054434</td>\n",
       "      <td>0.279390</td>\n",
       "      <td>-0.020639</td>\n",
       "      <td>0.243150</td>\n",
       "      <td>0.264796</td>\n",
       "      <td>0.220317</td>\n",
       "      <td>-0.661271</td>\n",
       "      <td>0.004058</td>\n",
       "      <td>-0.080679</td>\n",
       "      <td>0.004366</td>\n",
       "      <td>0.019465</td>\n",
       "      <td>0.094771</td>\n",
       "      <td>0.146036</td>\n",
       "      <td>-0.021389</td>\n",
       "      <td>-0.144670</td>\n",
       "      <td>-0.084616</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.228383</td>\n",
       "      <td>0.273049</td>\n",
       "      <td>0.105904</td>\n",
       "      <td>0.090459</td>\n",
       "      <td>0.078808</td>\n",
       "      <td>0.017052</td>\n",
       "      <td>-0.001444</td>\n",
       "      <td>-0.042871</td>\n",
       "      <td>-0.185015</td>\n",
       "      <td>-0.143501</td>\n",
       "      <td>-0.083164</td>\n",
       "      <td>-0.215523</td>\n",
       "      <td>0.065865</td>\n",
       "      <td>0.036069</td>\n",
       "      <td>-0.048287</td>\n",
       "      <td>-0.030766</td>\n",
       "      <td>0.159223</td>\n",
       "      <td>0.021503</td>\n",
       "      <td>-0.023944</td>\n",
       "      <td>-0.000012</td>\n",
       "      <td>-0.006413</td>\n",
       "      <td>-0.019178</td>\n",
       "      <td>-0.412989</td>\n",
       "      <td>-0.040880</td>\n",
       "      <td>0.047684</td>\n",
       "      <td>0.053352</td>\n",
       "      <td>-0.014144</td>\n",
       "      <td>0.030128</td>\n",
       "      <td>0.031226</td>\n",
       "      <td>0.064856</td>\n",
       "      <td>-0.060968</td>\n",
       "      <td>-0.111673</td>\n",
       "      <td>-0.078730</td>\n",
       "      <td>0.010319</td>\n",
       "      <td>-0.018640</td>\n",
       "      <td>-0.057861</td>\n",
       "      <td>0.059576</td>\n",
       "      <td>0.030077</td>\n",
       "      <td>-0.174754</td>\n",
       "      <td>0.116347</td>\n",
       "      <td>0.056874</td>\n",
       "      <td>0.226952</td>\n",
       "      <td>-0.161628</td>\n",
       "      <td>-0.040750</td>\n",
       "      <td>0.033497</td>\n",
       "      <td>0.141739</td>\n",
       "      <td>0.049109</td>\n",
       "      <td>0.147416</td>\n",
       "      <td>0.009644</td>\n",
       "      <td>0.081898</td>\n",
       "      <td>-0.116170</td>\n",
       "      <td>0.044023</td>\n",
       "      <td>0.138449</td>\n",
       "      <td>0.060729</td>\n",
       "      <td>-0.013011</td>\n",
       "      <td>0.214670</td>\n",
       "      <td>0.214921</td>\n",
       "      <td>0.163169</td>\n",
       "      <td>0.172829</td>\n",
       "      <td>0.094156</td>\n",
       "      <td>-0.078867</td>\n",
       "      <td>-0.005107</td>\n",
       "      <td>0.043990</td>\n",
       "      <td>-0.085132</td>\n",
       "      <td>-0.119136</td>\n",
       "      <td>-0.018261</td>\n",
       "      <td>0.049943</td>\n",
       "      <td>0.044731</td>\n",
       "      <td>-0.018016</td>\n",
       "      <td>-0.007514</td>\n",
       "      <td>-0.115282</td>\n",
       "      <td>-0.235770</td>\n",
       "      <td>-0.118667</td>\n",
       "      <td>-0.209248</td>\n",
       "      <td>-0.131729</td>\n",
       "      <td>0.048481</td>\n",
       "      <td>0.058296</td>\n",
       "      <td>-0.118652</td>\n",
       "      <td>0.118726</td>\n",
       "      <td>-0.014342</td>\n",
       "      <td>0.046267</td>\n",
       "      <td>-0.055623</td>\n",
       "      <td>0.024685</td>\n",
       "      <td>0.140289</td>\n",
       "      <td>0.394261</td>\n",
       "      <td>0.385146</td>\n",
       "      <td>0.351690</td>\n",
       "      <td>0.367435</td>\n",
       "      <td>0.234770</td>\n",
       "      <td>-0.444441</td>\n",
       "      <td>0.002180</td>\n",
       "      <td>-1.085298</td>\n",
       "      <td>-0.693637</td>\n",
       "      <td>0.139887</td>\n",
       "      <td>-0.116656</td>\n",
       "      <td>-0.188694</td>\n",
       "      <td>-0.073202</td>\n",
       "      <td>-0.152716</td>\n",
       "      <td>-0.100834</td>\n",
       "      <td>-0.078823</td>\n",
       "      <td>-0.043472</td>\n",
       "      <td>-0.060758</td>\n",
       "      <td>-0.043201</td>\n",
       "      <td>-0.029732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.099074</td>\n",
       "      <td>-0.000187</td>\n",
       "      <td>-0.735145</td>\n",
       "      <td>0.047877</td>\n",
       "      <td>0.258190</td>\n",
       "      <td>-0.033020</td>\n",
       "      <td>0.967883</td>\n",
       "      <td>0.862862</td>\n",
       "      <td>0.696593</td>\n",
       "      <td>-0.645765</td>\n",
       "      <td>0.140856</td>\n",
       "      <td>0.283935</td>\n",
       "      <td>0.570744</td>\n",
       "      <td>-1.159370</td>\n",
       "      <td>0.978186</td>\n",
       "      <td>-0.419176</td>\n",
       "      <td>0.463465</td>\n",
       "      <td>-0.773326</td>\n",
       "      <td>0.302468</td>\n",
       "      <td>-0.051802</td>\n",
       "      <td>-1.178247</td>\n",
       "      <td>0.609890</td>\n",
       "      <td>0.283948</td>\n",
       "      <td>-1.592555</td>\n",
       "      <td>-1.397972</td>\n",
       "      <td>-0.374131</td>\n",
       "      <td>0.283616</td>\n",
       "      <td>-0.092007</td>\n",
       "      <td>-0.077518</td>\n",
       "      <td>-0.377802</td>\n",
       "      <td>0.432960</td>\n",
       "      <td>0.353201</td>\n",
       "      <td>-0.133574</td>\n",
       "      <td>0.841658</td>\n",
       "      <td>0.370396</td>\n",
       "      <td>0.034232</td>\n",
       "      <td>1.166267</td>\n",
       "      <td>-0.152138</td>\n",
       "      <td>-0.716958</td>\n",
       "      <td>0.110154</td>\n",
       "      <td>-0.274861</td>\n",
       "      <td>-0.360281</td>\n",
       "      <td>0.381913</td>\n",
       "      <td>1.344522</td>\n",
       "      <td>-0.107604</td>\n",
       "      <td>-0.255337</td>\n",
       "      <td>-0.188521</td>\n",
       "      <td>-0.960975</td>\n",
       "      <td>0.158200</td>\n",
       "      <td>0.104043</td>\n",
       "      <td>0.086454</td>\n",
       "      <td>-0.048871</td>\n",
       "      <td>-0.008113</td>\n",
       "      <td>-0.005000</td>\n",
       "      <td>-0.077138</td>\n",
       "      <td>0.052282</td>\n",
       "      <td>-0.097806</td>\n",
       "      <td>0.100464</td>\n",
       "      <td>0.021533</td>\n",
       "      <td>0.120672</td>\n",
       "      <td>0.198293</td>\n",
       "      <td>0.173212</td>\n",
       "      <td>0.021254</td>\n",
       "      <td>-0.097101</td>\n",
       "      <td>-0.067666</td>\n",
       "      <td>0.004304</td>\n",
       "      <td>0.005608</td>\n",
       "      <td>0.035283</td>\n",
       "      <td>0.008703</td>\n",
       "      <td>0.008696</td>\n",
       "      <td>-0.005398</td>\n",
       "      <td>0.093725</td>\n",
       "      <td>0.069030</td>\n",
       "      <td>-0.124414</td>\n",
       "      <td>-0.311311</td>\n",
       "      <td>0.037271</td>\n",
       "      <td>0.171291</td>\n",
       "      <td>-0.586120</td>\n",
       "      <td>0.190105</td>\n",
       "      <td>0.014719</td>\n",
       "      <td>-0.009434</td>\n",
       "      <td>0.319134</td>\n",
       "      <td>0.284801</td>\n",
       "      <td>-0.265436</td>\n",
       "      <td>-0.419068</td>\n",
       "      <td>0.152229</td>\n",
       "      <td>0.368996</td>\n",
       "      <td>0.067237</td>\n",
       "      <td>0.314249</td>\n",
       "      <td>-0.005522</td>\n",
       "      <td>0.255806</td>\n",
       "      <td>0.266072</td>\n",
       "      <td>0.245764</td>\n",
       "      <td>-0.586120</td>\n",
       "      <td>0.032146</td>\n",
       "      <td>-0.072947</td>\n",
       "      <td>0.005121</td>\n",
       "      <td>0.023039</td>\n",
       "      <td>0.097960</td>\n",
       "      <td>0.151011</td>\n",
       "      <td>-0.014003</td>\n",
       "      <td>-0.136996</td>\n",
       "      <td>-0.079119</td>\n",
       "      <td>0.002959</td>\n",
       "      <td>0.246359</td>\n",
       "      <td>0.292819</td>\n",
       "      <td>0.122321</td>\n",
       "      <td>0.102525</td>\n",
       "      <td>0.087487</td>\n",
       "      <td>0.020139</td>\n",
       "      <td>0.000933</td>\n",
       "      <td>-0.031747</td>\n",
       "      <td>-0.172752</td>\n",
       "      <td>-0.140658</td>\n",
       "      <td>-0.082593</td>\n",
       "      <td>-0.213108</td>\n",
       "      <td>0.070128</td>\n",
       "      <td>0.040012</td>\n",
       "      <td>-0.043365</td>\n",
       "      <td>-0.026241</td>\n",
       "      <td>0.161223</td>\n",
       "      <td>0.024037</td>\n",
       "      <td>-0.019853</td>\n",
       "      <td>0.004169</td>\n",
       "      <td>-0.001506</td>\n",
       "      <td>-0.018784</td>\n",
       "      <td>-0.382724</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>0.050196</td>\n",
       "      <td>0.055800</td>\n",
       "      <td>-0.013725</td>\n",
       "      <td>0.030577</td>\n",
       "      <td>0.031748</td>\n",
       "      <td>0.066653</td>\n",
       "      <td>-0.059599</td>\n",
       "      <td>-0.111576</td>\n",
       "      <td>-0.077320</td>\n",
       "      <td>0.010843</td>\n",
       "      <td>-0.018212</td>\n",
       "      <td>-0.056290</td>\n",
       "      <td>0.064058</td>\n",
       "      <td>0.030721</td>\n",
       "      <td>-0.172487</td>\n",
       "      <td>0.119318</td>\n",
       "      <td>0.061314</td>\n",
       "      <td>0.230923</td>\n",
       "      <td>-0.159934</td>\n",
       "      <td>-0.040261</td>\n",
       "      <td>0.034084</td>\n",
       "      <td>0.143755</td>\n",
       "      <td>0.049711</td>\n",
       "      <td>0.149144</td>\n",
       "      <td>0.010018</td>\n",
       "      <td>0.082071</td>\n",
       "      <td>-0.114579</td>\n",
       "      <td>0.044596</td>\n",
       "      <td>0.148069</td>\n",
       "      <td>0.062519</td>\n",
       "      <td>0.001156</td>\n",
       "      <td>0.222311</td>\n",
       "      <td>0.232898</td>\n",
       "      <td>0.182239</td>\n",
       "      <td>0.192732</td>\n",
       "      <td>0.113664</td>\n",
       "      <td>-0.062274</td>\n",
       "      <td>0.013122</td>\n",
       "      <td>0.061916</td>\n",
       "      <td>-0.079867</td>\n",
       "      <td>-0.117135</td>\n",
       "      <td>-0.014927</td>\n",
       "      <td>0.054912</td>\n",
       "      <td>0.049005</td>\n",
       "      <td>-0.014731</td>\n",
       "      <td>-0.006381</td>\n",
       "      <td>-0.111275</td>\n",
       "      <td>-0.230214</td>\n",
       "      <td>-0.110931</td>\n",
       "      <td>-0.199105</td>\n",
       "      <td>-0.119619</td>\n",
       "      <td>0.060952</td>\n",
       "      <td>0.073115</td>\n",
       "      <td>-0.100095</td>\n",
       "      <td>0.130059</td>\n",
       "      <td>0.039966</td>\n",
       "      <td>0.102938</td>\n",
       "      <td>-0.000670</td>\n",
       "      <td>0.085973</td>\n",
       "      <td>0.200701</td>\n",
       "      <td>0.454266</td>\n",
       "      <td>0.443142</td>\n",
       "      <td>0.406621</td>\n",
       "      <td>0.421664</td>\n",
       "      <td>0.286914</td>\n",
       "      <td>-0.407969</td>\n",
       "      <td>0.013594</td>\n",
       "      <td>-0.866375</td>\n",
       "      <td>-0.549317</td>\n",
       "      <td>0.294831</td>\n",
       "      <td>-0.095106</td>\n",
       "      <td>-0.152495</td>\n",
       "      <td>-0.058833</td>\n",
       "      <td>-0.123400</td>\n",
       "      <td>-0.081197</td>\n",
       "      <td>-0.062895</td>\n",
       "      <td>-0.034450</td>\n",
       "      <td>-0.048215</td>\n",
       "      <td>-0.034031</td>\n",
       "      <td>-0.023276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-0.094536</td>\n",
       "      <td>0.002285</td>\n",
       "      <td>-0.732159</td>\n",
       "      <td>0.048609</td>\n",
       "      <td>0.269275</td>\n",
       "      <td>-0.003496</td>\n",
       "      <td>1.027103</td>\n",
       "      <td>0.913792</td>\n",
       "      <td>0.724630</td>\n",
       "      <td>-0.491560</td>\n",
       "      <td>0.166589</td>\n",
       "      <td>0.287234</td>\n",
       "      <td>0.682439</td>\n",
       "      <td>-1.043720</td>\n",
       "      <td>1.088137</td>\n",
       "      <td>-0.375113</td>\n",
       "      <td>0.499075</td>\n",
       "      <td>-0.603647</td>\n",
       "      <td>0.310981</td>\n",
       "      <td>-0.018152</td>\n",
       "      <td>-0.990841</td>\n",
       "      <td>0.622465</td>\n",
       "      <td>0.300682</td>\n",
       "      <td>-1.547228</td>\n",
       "      <td>-1.359908</td>\n",
       "      <td>-0.297110</td>\n",
       "      <td>0.312899</td>\n",
       "      <td>-0.050476</td>\n",
       "      <td>-0.025135</td>\n",
       "      <td>-0.338199</td>\n",
       "      <td>0.556515</td>\n",
       "      <td>0.364898</td>\n",
       "      <td>-0.064999</td>\n",
       "      <td>0.897388</td>\n",
       "      <td>0.400549</td>\n",
       "      <td>0.052710</td>\n",
       "      <td>1.237696</td>\n",
       "      <td>-0.104815</td>\n",
       "      <td>-0.701182</td>\n",
       "      <td>0.126186</td>\n",
       "      <td>-0.230931</td>\n",
       "      <td>-0.316981</td>\n",
       "      <td>0.383330</td>\n",
       "      <td>1.346239</td>\n",
       "      <td>-0.079403</td>\n",
       "      <td>-0.246883</td>\n",
       "      <td>-0.178542</td>\n",
       "      <td>-0.864840</td>\n",
       "      <td>0.160367</td>\n",
       "      <td>0.106233</td>\n",
       "      <td>0.088906</td>\n",
       "      <td>-0.046090</td>\n",
       "      <td>-0.003330</td>\n",
       "      <td>0.000781</td>\n",
       "      <td>-0.049038</td>\n",
       "      <td>0.057059</td>\n",
       "      <td>-0.090908</td>\n",
       "      <td>0.102318</td>\n",
       "      <td>0.024399</td>\n",
       "      <td>0.124087</td>\n",
       "      <td>0.202959</td>\n",
       "      <td>0.176155</td>\n",
       "      <td>0.024213</td>\n",
       "      <td>-0.079622</td>\n",
       "      <td>-0.043331</td>\n",
       "      <td>0.023668</td>\n",
       "      <td>0.025699</td>\n",
       "      <td>0.050680</td>\n",
       "      <td>0.018176</td>\n",
       "      <td>0.014497</td>\n",
       "      <td>0.000899</td>\n",
       "      <td>0.100688</td>\n",
       "      <td>0.079714</td>\n",
       "      <td>-0.118467</td>\n",
       "      <td>-0.305469</td>\n",
       "      <td>0.074938</td>\n",
       "      <td>0.180215</td>\n",
       "      <td>-0.466177</td>\n",
       "      <td>0.197081</td>\n",
       "      <td>0.019583</td>\n",
       "      <td>-0.003237</td>\n",
       "      <td>0.335041</td>\n",
       "      <td>0.300857</td>\n",
       "      <td>-0.240819</td>\n",
       "      <td>-0.340730</td>\n",
       "      <td>0.163235</td>\n",
       "      <td>0.370037</td>\n",
       "      <td>0.072860</td>\n",
       "      <td>0.332654</td>\n",
       "      <td>0.018177</td>\n",
       "      <td>0.261476</td>\n",
       "      <td>0.266692</td>\n",
       "      <td>0.257403</td>\n",
       "      <td>-0.466177</td>\n",
       "      <td>0.049869</td>\n",
       "      <td>-0.057819</td>\n",
       "      <td>0.006072</td>\n",
       "      <td>0.023685</td>\n",
       "      <td>0.104191</td>\n",
       "      <td>0.160211</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>-0.121879</td>\n",
       "      <td>-0.067914</td>\n",
       "      <td>0.003851</td>\n",
       "      <td>0.253352</td>\n",
       "      <td>0.300592</td>\n",
       "      <td>0.129650</td>\n",
       "      <td>0.108149</td>\n",
       "      <td>0.091328</td>\n",
       "      <td>0.021316</td>\n",
       "      <td>0.003223</td>\n",
       "      <td>-0.010239</td>\n",
       "      <td>-0.147921</td>\n",
       "      <td>-0.135146</td>\n",
       "      <td>-0.081690</td>\n",
       "      <td>-0.207699</td>\n",
       "      <td>0.075909</td>\n",
       "      <td>0.046194</td>\n",
       "      <td>-0.035901</td>\n",
       "      <td>-0.020713</td>\n",
       "      <td>0.163679</td>\n",
       "      <td>0.026964</td>\n",
       "      <td>-0.013360</td>\n",
       "      <td>0.009577</td>\n",
       "      <td>0.005602</td>\n",
       "      <td>-0.018551</td>\n",
       "      <td>-0.314237</td>\n",
       "      <td>-0.040455</td>\n",
       "      <td>0.050749</td>\n",
       "      <td>0.056068</td>\n",
       "      <td>-0.013543</td>\n",
       "      <td>0.030703</td>\n",
       "      <td>0.032359</td>\n",
       "      <td>0.067037</td>\n",
       "      <td>-0.057609</td>\n",
       "      <td>-0.111432</td>\n",
       "      <td>-0.074705</td>\n",
       "      <td>0.011355</td>\n",
       "      <td>-0.018018</td>\n",
       "      <td>-0.053576</td>\n",
       "      <td>0.065370</td>\n",
       "      <td>0.031281</td>\n",
       "      <td>-0.167121</td>\n",
       "      <td>0.119940</td>\n",
       "      <td>0.062701</td>\n",
       "      <td>0.231628</td>\n",
       "      <td>-0.156531</td>\n",
       "      <td>-0.040167</td>\n",
       "      <td>0.034800</td>\n",
       "      <td>0.144082</td>\n",
       "      <td>0.050110</td>\n",
       "      <td>0.149402</td>\n",
       "      <td>0.010159</td>\n",
       "      <td>0.082366</td>\n",
       "      <td>-0.111522</td>\n",
       "      <td>0.044832</td>\n",
       "      <td>0.151764</td>\n",
       "      <td>0.062779</td>\n",
       "      <td>0.012374</td>\n",
       "      <td>0.224328</td>\n",
       "      <td>0.234671</td>\n",
       "      <td>0.185421</td>\n",
       "      <td>0.198659</td>\n",
       "      <td>0.121554</td>\n",
       "      <td>-0.053577</td>\n",
       "      <td>0.025194</td>\n",
       "      <td>0.072940</td>\n",
       "      <td>-0.076253</td>\n",
       "      <td>-0.113114</td>\n",
       "      <td>-0.011217</td>\n",
       "      <td>0.059141</td>\n",
       "      <td>0.052715</td>\n",
       "      <td>-0.010908</td>\n",
       "      <td>-0.001271</td>\n",
       "      <td>-0.093784</td>\n",
       "      <td>-0.210836</td>\n",
       "      <td>-0.090560</td>\n",
       "      <td>-0.176242</td>\n",
       "      <td>-0.096743</td>\n",
       "      <td>0.081702</td>\n",
       "      <td>0.093693</td>\n",
       "      <td>-0.075900</td>\n",
       "      <td>0.142297</td>\n",
       "      <td>0.088369</td>\n",
       "      <td>0.152398</td>\n",
       "      <td>0.047416</td>\n",
       "      <td>0.132830</td>\n",
       "      <td>0.245014</td>\n",
       "      <td>0.495443</td>\n",
       "      <td>0.480879</td>\n",
       "      <td>0.439288</td>\n",
       "      <td>0.450130</td>\n",
       "      <td>0.311548</td>\n",
       "      <td>-0.334594</td>\n",
       "      <td>0.017788</td>\n",
       "      <td>-0.563256</td>\n",
       "      <td>-0.355900</td>\n",
       "      <td>0.420638</td>\n",
       "      <td>-0.065959</td>\n",
       "      <td>-0.102903</td>\n",
       "      <td>-0.039624</td>\n",
       "      <td>-0.084115</td>\n",
       "      <td>-0.055139</td>\n",
       "      <td>-0.041781</td>\n",
       "      <td>-0.022500</td>\n",
       "      <td>-0.031736</td>\n",
       "      <td>-0.021985</td>\n",
       "      <td>-0.014875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.003442</td>\n",
       "      <td>0.004406</td>\n",
       "      <td>-0.103161</td>\n",
       "      <td>0.053764</td>\n",
       "      <td>0.287466</td>\n",
       "      <td>0.050015</td>\n",
       "      <td>1.070732</td>\n",
       "      <td>0.950335</td>\n",
       "      <td>0.743367</td>\n",
       "      <td>-0.002432</td>\n",
       "      <td>0.311848</td>\n",
       "      <td>0.288506</td>\n",
       "      <td>0.757097</td>\n",
       "      <td>0.019560</td>\n",
       "      <td>1.161579</td>\n",
       "      <td>0.049803</td>\n",
       "      <td>0.517409</td>\n",
       "      <td>-0.003094</td>\n",
       "      <td>0.314580</td>\n",
       "      <td>0.010316</td>\n",
       "      <td>-0.013855</td>\n",
       "      <td>0.629058</td>\n",
       "      <td>0.310096</td>\n",
       "      <td>-0.542830</td>\n",
       "      <td>-0.312957</td>\n",
       "      <td>0.002659</td>\n",
       "      <td>0.345242</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>0.057425</td>\n",
       "      <td>0.008046</td>\n",
       "      <td>0.670313</td>\n",
       "      <td>0.373449</td>\n",
       "      <td>0.013017</td>\n",
       "      <td>0.948306</td>\n",
       "      <td>0.446700</td>\n",
       "      <td>0.067898</td>\n",
       "      <td>1.286998</td>\n",
       "      <td>0.014851</td>\n",
       "      <td>-0.039185</td>\n",
       "      <td>0.140433</td>\n",
       "      <td>0.026971</td>\n",
       "      <td>0.062586</td>\n",
       "      <td>0.389201</td>\n",
       "      <td>1.349733</td>\n",
       "      <td>-0.003044</td>\n",
       "      <td>-0.060181</td>\n",
       "      <td>-0.088382</td>\n",
       "      <td>-0.039822</td>\n",
       "      <td>0.161758</td>\n",
       "      <td>0.107225</td>\n",
       "      <td>0.090304</td>\n",
       "      <td>-0.039228</td>\n",
       "      <td>-0.000345</td>\n",
       "      <td>0.004865</td>\n",
       "      <td>-0.000186</td>\n",
       "      <td>0.060180</td>\n",
       "      <td>-0.015970</td>\n",
       "      <td>0.104036</td>\n",
       "      <td>0.025816</td>\n",
       "      <td>0.125016</td>\n",
       "      <td>0.205374</td>\n",
       "      <td>0.177142</td>\n",
       "      <td>0.025693</td>\n",
       "      <td>-0.000123</td>\n",
       "      <td>0.041797</td>\n",
       "      <td>0.074039</td>\n",
       "      <td>0.064187</td>\n",
       "      <td>0.078122</td>\n",
       "      <td>0.030141</td>\n",
       "      <td>0.019069</td>\n",
       "      <td>0.003389</td>\n",
       "      <td>0.103894</td>\n",
       "      <td>0.084891</td>\n",
       "      <td>-0.022226</td>\n",
       "      <td>-0.044306</td>\n",
       "      <td>0.128527</td>\n",
       "      <td>0.183912</td>\n",
       "      <td>-0.014778</td>\n",
       "      <td>0.203089</td>\n",
       "      <td>0.035592</td>\n",
       "      <td>0.007758</td>\n",
       "      <td>0.344423</td>\n",
       "      <td>0.310619</td>\n",
       "      <td>-0.003460</td>\n",
       "      <td>-0.011645</td>\n",
       "      <td>0.169776</td>\n",
       "      <td>0.373714</td>\n",
       "      <td>0.076516</td>\n",
       "      <td>0.348250</td>\n",
       "      <td>0.070421</td>\n",
       "      <td>0.265622</td>\n",
       "      <td>0.268473</td>\n",
       "      <td>0.265839</td>\n",
       "      <td>-0.014778</td>\n",
       "      <td>0.061989</td>\n",
       "      <td>-0.002760</td>\n",
       "      <td>0.006781</td>\n",
       "      <td>0.024461</td>\n",
       "      <td>0.108556</td>\n",
       "      <td>0.169342</td>\n",
       "      <td>0.029668</td>\n",
       "      <td>-0.012936</td>\n",
       "      <td>-0.002344</td>\n",
       "      <td>0.004521</td>\n",
       "      <td>0.255897</td>\n",
       "      <td>0.303934</td>\n",
       "      <td>0.131761</td>\n",
       "      <td>0.109783</td>\n",
       "      <td>0.092676</td>\n",
       "      <td>0.022240</td>\n",
       "      <td>0.017545</td>\n",
       "      <td>0.024959</td>\n",
       "      <td>-0.002162</td>\n",
       "      <td>-0.019207</td>\n",
       "      <td>-0.021638</td>\n",
       "      <td>-0.025687</td>\n",
       "      <td>0.080735</td>\n",
       "      <td>0.054891</td>\n",
       "      <td>-0.002879</td>\n",
       "      <td>-0.007392</td>\n",
       "      <td>0.165032</td>\n",
       "      <td>0.028243</td>\n",
       "      <td>-0.005955</td>\n",
       "      <td>0.019285</td>\n",
       "      <td>0.019870</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>-0.002745</td>\n",
       "      <td>-0.011792</td>\n",
       "      <td>0.051429</td>\n",
       "      <td>0.056861</td>\n",
       "      <td>-0.002645</td>\n",
       "      <td>0.030904</td>\n",
       "      <td>0.032718</td>\n",
       "      <td>0.067543</td>\n",
       "      <td>0.005494</td>\n",
       "      <td>-0.014402</td>\n",
       "      <td>-0.015876</td>\n",
       "      <td>0.013242</td>\n",
       "      <td>-0.001949</td>\n",
       "      <td>-0.003553</td>\n",
       "      <td>0.066918</td>\n",
       "      <td>0.031701</td>\n",
       "      <td>-0.008170</td>\n",
       "      <td>0.120873</td>\n",
       "      <td>0.063678</td>\n",
       "      <td>0.232375</td>\n",
       "      <td>-0.015394</td>\n",
       "      <td>-0.003601</td>\n",
       "      <td>0.035296</td>\n",
       "      <td>0.144682</td>\n",
       "      <td>0.050401</td>\n",
       "      <td>0.149935</td>\n",
       "      <td>0.010492</td>\n",
       "      <td>0.082707</td>\n",
       "      <td>-0.000525</td>\n",
       "      <td>0.045096</td>\n",
       "      <td>0.154120</td>\n",
       "      <td>0.063064</td>\n",
       "      <td>0.032141</td>\n",
       "      <td>0.226228</td>\n",
       "      <td>0.240995</td>\n",
       "      <td>0.190733</td>\n",
       "      <td>0.203314</td>\n",
       "      <td>0.125507</td>\n",
       "      <td>-0.024520</td>\n",
       "      <td>0.033160</td>\n",
       "      <td>0.081455</td>\n",
       "      <td>-0.011411</td>\n",
       "      <td>-0.015921</td>\n",
       "      <td>0.013114</td>\n",
       "      <td>0.099564</td>\n",
       "      <td>0.061464</td>\n",
       "      <td>0.011213</td>\n",
       "      <td>0.045423</td>\n",
       "      <td>0.018284</td>\n",
       "      <td>-0.013454</td>\n",
       "      <td>0.010990</td>\n",
       "      <td>-0.019620</td>\n",
       "      <td>-0.009579</td>\n",
       "      <td>0.100942</td>\n",
       "      <td>0.108880</td>\n",
       "      <td>-0.005205</td>\n",
       "      <td>0.151041</td>\n",
       "      <td>0.128460</td>\n",
       "      <td>0.193428</td>\n",
       "      <td>0.087252</td>\n",
       "      <td>0.170450</td>\n",
       "      <td>0.279436</td>\n",
       "      <td>0.526268</td>\n",
       "      <td>0.507962</td>\n",
       "      <td>0.463546</td>\n",
       "      <td>0.471874</td>\n",
       "      <td>0.332347</td>\n",
       "      <td>-0.007056</td>\n",
       "      <td>0.020305</td>\n",
       "      <td>-0.005755</td>\n",
       "      <td>-0.005202</td>\n",
       "      <td>0.572149</td>\n",
       "      <td>-0.001606</td>\n",
       "      <td>-0.001896</td>\n",
       "      <td>-0.001042</td>\n",
       "      <td>-0.002087</td>\n",
       "      <td>-0.001392</td>\n",
       "      <td>-0.000986</td>\n",
       "      <td>-0.000533</td>\n",
       "      <td>-0.000718</td>\n",
       "      <td>-0.000508</td>\n",
       "      <td>-0.000340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        playoffs  shot_distance  last_5_sec_in_period  home_play  \\\n",
       "count  40.000000      40.000000             40.000000  40.000000   \n",
       "mean   -0.093053      -0.000727             -0.712689   0.048389   \n",
       "std     0.018136       0.003649              0.101160   0.001487   \n",
       "min    -0.101460      -0.013534             -0.736455   0.045628   \n",
       "25%    -0.100388      -0.003436             -0.736014   0.047571   \n",
       "50%    -0.099074      -0.000187             -0.735145   0.047877   \n",
       "75%    -0.094536       0.002285             -0.732159   0.048609   \n",
       "max     0.003442       0.004406             -0.103161   0.053764   \n",
       "\n",
       "       action_type_Alley Oop Dunk Shot  action_type_Alley Oop Layup shot  \\\n",
       "count                        40.000000                         40.000000   \n",
       "mean                          0.245134                         -0.024445   \n",
       "std                           0.045950                          0.033333   \n",
       "min                           0.024030                         -0.064598   \n",
       "25%                           0.241579                         -0.051271   \n",
       "50%                           0.258190                         -0.033020   \n",
       "75%                           0.269275                         -0.003496   \n",
       "max                           0.287466                          0.050015   \n",
       "\n",
       "       action_type_Driving Dunk Shot  \\\n",
       "count                      40.000000   \n",
       "mean                        0.899716   \n",
       "std                         0.198034   \n",
       "min                         0.070274   \n",
       "25%                         0.856513   \n",
       "50%                         0.967883   \n",
       "75%                         1.027103   \n",
       "max                         1.070732   \n",
       "\n",
       "       action_type_Driving Finger Roll Layup Shot  \\\n",
       "count                                   40.000000   \n",
       "mean                                     0.783623   \n",
       "std                                      0.205713   \n",
       "min                                      0.015647   \n",
       "25%                                      0.737975   \n",
       "50%                                      0.862862   \n",
       "75%                                      0.913792   \n",
       "max                                      0.950335   \n",
       "\n",
       "       action_type_Driving Finger Roll Shot  action_type_Driving Jump shot  \\\n",
       "count                             40.000000                      40.000000   \n",
       "mean                               0.636809                      -0.574973   \n",
       "std                                0.151185                       0.197234   \n",
       "min                                0.016555                      -0.781493   \n",
       "25%                                0.619739                      -0.722235   \n",
       "50%                                0.696593                      -0.645765   \n",
       "75%                                0.724630                      -0.491560   \n",
       "max                                0.743367                      -0.002432   \n",
       "\n",
       "       action_type_Driving Layup Shot  action_type_Driving Reverse Layup Shot  \\\n",
       "count                       40.000000                               40.000000   \n",
       "mean                         0.155241                                0.269374   \n",
       "std                          0.044420                                0.048643   \n",
       "min                          0.109979                                0.012166   \n",
       "25%                          0.125620                                0.278531   \n",
       "50%                          0.140856                                0.283935   \n",
       "75%                          0.166589                                0.287234   \n",
       "max                          0.311848                                0.288506   \n",
       "\n",
       "       action_type_Driving Slam Dunk Shot  action_type_Dunk Shot  \\\n",
       "count                           40.000000              40.000000   \n",
       "mean                             0.522294              -1.052781   \n",
       "std                              0.193077               0.263196   \n",
       "min                              0.012264              -1.226231   \n",
       "25%                              0.408558              -1.202162   \n",
       "50%                              0.570744              -1.159370   \n",
       "75%                              0.682439              -1.043720   \n",
       "max                              0.757097               0.019560   \n",
       "\n",
       "       action_type_Fadeaway Bank shot  action_type_Fadeaway Jump Shot  \\\n",
       "count                       40.000000                       40.000000   \n",
       "mean                         0.879697                       -0.391270   \n",
       "std                          0.285817                        0.093184   \n",
       "min                          0.010025                       -0.466938   \n",
       "25%                          0.763475                       -0.445905   \n",
       "50%                          0.978186                       -0.419176   \n",
       "75%                          1.088137                       -0.375113   \n",
       "max                          1.161579                        0.049803   \n",
       "\n",
       "       action_type_Finger Roll Layup Shot  action_type_Finger Roll Shot  \\\n",
       "count                           40.000000                     40.000000   \n",
       "mean                             0.415424                     -0.687313   \n",
       "std                              0.122196                      0.226901   \n",
       "min                              0.006243                     -0.906866   \n",
       "25%                              0.377956                     -0.848998   \n",
       "50%                              0.463465                     -0.773326   \n",
       "75%                              0.499075                     -0.603647   \n",
       "max                              0.517409                     -0.003094   \n",
       "\n",
       "       action_type_Floating Jump shot  action_type_Follow Up Dunk Shot  \\\n",
       "count                       40.000000                        40.000000   \n",
       "mean                         0.289430                        -0.046363   \n",
       "std                          0.051386                         0.033601   \n",
       "min                          0.016589                        -0.093926   \n",
       "25%                          0.294627                        -0.076487   \n",
       "50%                          0.302468                        -0.051802   \n",
       "75%                          0.310981                        -0.018152   \n",
       "max                          0.314580                         0.010316   \n",
       "\n",
       "       action_type_Hook Shot  action_type_Jump Bank Shot  \\\n",
       "count              40.000000                   40.000000   \n",
       "mean               -1.074137                    0.592894   \n",
       "std                 0.292607                    0.088484   \n",
       "min                -1.338320                    0.071413   \n",
       "25%                -1.268141                    0.598310   \n",
       "50%                -1.178247                    0.609890   \n",
       "75%                -0.990841                    0.622465   \n",
       "max                -0.013855                    0.629058   \n",
       "\n",
       "       action_type_Jump Hook Shot  action_type_Jump Shot  \\\n",
       "count                   40.000000              40.000000   \n",
       "mean                     0.251523              -1.549020   \n",
       "std                      0.074990               0.174891   \n",
       "min                      0.003492              -1.640757   \n",
       "25%                      0.231887              -1.619009   \n",
       "50%                      0.283948              -1.592555   \n",
       "75%                      0.300682              -1.547228   \n",
       "max                      0.310096              -0.542830   \n",
       "\n",
       "       action_type_Layup Shot  action_type_Other  \\\n",
       "count               40.000000          40.000000   \n",
       "mean                -1.349372          -0.335740   \n",
       "std                  0.180457           0.109667   \n",
       "min                 -1.432840          -0.440416   \n",
       "25%                 -1.416126          -0.416060   \n",
       "50%                 -1.397972          -0.374131   \n",
       "75%                 -1.359908          -0.297110   \n",
       "max                 -0.312957           0.002659   \n",
       "\n",
       "       action_type_Pullup Jump shot  action_type_Putback Layup Shot  \\\n",
       "count                     40.000000                       40.000000   \n",
       "mean                       0.284715                       -0.082439   \n",
       "std                        0.044644                        0.043688   \n",
       "min                        0.083998                       -0.140310   \n",
       "25%                        0.262292                       -0.120786   \n",
       "50%                        0.283616                       -0.092007   \n",
       "75%                        0.312899                       -0.050476   \n",
       "max                        0.345242                        0.001021   \n",
       "\n",
       "       action_type_Reverse Dunk Shot  action_type_Reverse Layup Shot  \\\n",
       "count                      40.000000                       40.000000   \n",
       "mean                       -0.056372                       -0.347727   \n",
       "std                         0.050554                        0.085624   \n",
       "min                        -0.105802                       -0.414669   \n",
       "25%                        -0.095928                       -0.396533   \n",
       "50%                        -0.077518                       -0.377802   \n",
       "75%                        -0.025135                       -0.338199   \n",
       "max                         0.057425                        0.008046   \n",
       "\n",
       "       action_type_Reverse Slam Dunk Shot  action_type_Running Bank shot  \\\n",
       "count                           40.000000                      40.000000   \n",
       "mean                             0.400066                       0.323066   \n",
       "std                              0.183174                       0.074092   \n",
       "min                              0.004771                       0.012466   \n",
       "25%                              0.269718                       0.314604   \n",
       "50%                              0.432960                       0.353201   \n",
       "75%                              0.556515                       0.364898   \n",
       "max                              0.670313                       0.373449   \n",
       "\n",
       "       action_type_Running Dunk Shot  action_type_Running Hook Shot  \\\n",
       "count                      40.000000                      40.000000   \n",
       "mean                       -0.116988                       0.759172   \n",
       "std                         0.068937                       0.216152   \n",
       "min                        -0.205913                       0.010456   \n",
       "25%                        -0.174804                       0.704857   \n",
       "50%                        -0.133574                       0.841658   \n",
       "75%                        -0.064999                       0.897388   \n",
       "max                         0.013017                       0.948306   \n",
       "\n",
       "       action_type_Running Jump Shot  action_type_Running Layup Shot  \\\n",
       "count                      40.000000                       40.000000   \n",
       "mean                        0.372647                        0.036409   \n",
       "std                         0.049740                        0.018790   \n",
       "min                         0.145004                        0.005345   \n",
       "25%                         0.349169                        0.021097   \n",
       "50%                         0.370396                        0.034232   \n",
       "75%                         0.400549                        0.052710   \n",
       "max                         0.446700                        0.067898   \n",
       "\n",
       "       action_type_Slam Dunk Shot  action_type_Step Back Jump shot  \\\n",
       "count                   40.000000                        40.000000   \n",
       "mean                     1.084993                        -0.134388   \n",
       "std                      0.236456                         0.060634   \n",
       "min                      0.091378                        -0.204374   \n",
       "25%                      1.032390                        -0.181794   \n",
       "50%                      1.166267                        -0.152138   \n",
       "75%                      1.237696                        -0.104815   \n",
       "max                      1.286998                         0.014851   \n",
       "\n",
       "       action_type_Tip Shot  action_type_Turnaround Bank shot  \\\n",
       "count             40.000000                         40.000000   \n",
       "mean              -0.690061                          0.109589   \n",
       "std                0.114408                          0.022559   \n",
       "min               -0.740734                          0.014449   \n",
       "25%               -0.732697                          0.097057   \n",
       "50%               -0.716958                          0.110154   \n",
       "75%               -0.701182                          0.126186   \n",
       "max               -0.039185                          0.140433   \n",
       "\n",
       "       action_type_Turnaround Fadeaway shot  action_type_Turnaround Jump Shot  \\\n",
       "count                             40.000000                         40.000000   \n",
       "mean                              -0.252588                         -0.334093   \n",
       "std                                0.073044                          0.087009   \n",
       "min                               -0.323097                         -0.407454   \n",
       "25%                               -0.302313                         -0.386184   \n",
       "50%                               -0.274861                         -0.360281   \n",
       "75%                               -0.230931                         -0.316981   \n",
       "max                                0.026971                          0.062586   \n",
       "\n",
       "       combined_shot_type_Bank Shot  combined_shot_type_Dunk  \\\n",
       "count                     40.000000                40.000000   \n",
       "mean                       0.365711                 1.291626   \n",
       "std                        0.059987                 0.182201   \n",
       "min                        0.029669                 0.241725   \n",
       "25%                        0.379280                 1.327187   \n",
       "50%                        0.381913                 1.344522   \n",
       "75%                        0.383330                 1.346239   \n",
       "max                        0.389201                 1.349733   \n",
       "\n",
       "       combined_shot_type_Hook Shot  combined_shot_type_Jump Shot  \\\n",
       "count                     40.000000                     40.000000   \n",
       "mean                      -0.113032                     -0.242881   \n",
       "std                        0.046063                      0.035430   \n",
       "min                       -0.192241                     -0.259842   \n",
       "25%                       -0.148950                     -0.258476   \n",
       "50%                       -0.107604                     -0.255337   \n",
       "75%                       -0.079403                     -0.246883   \n",
       "max                       -0.003044                     -0.060181   \n",
       "\n",
       "       combined_shot_type_Layup  combined_shot_type_Tip Shot   period_1  \\\n",
       "count                 40.000000                    40.000000  40.000000   \n",
       "mean                  -0.183500                    -0.906175   0.155511   \n",
       "std                    0.018572                     0.188227   0.015474   \n",
       "min                   -0.199945                    -1.076019   0.062283   \n",
       "25%                   -0.193834                    -1.020281   0.156321   \n",
       "50%                   -0.188521                    -0.960975   0.158200   \n",
       "75%                   -0.178542                    -0.864840   0.160367   \n",
       "max                   -0.088382                    -0.039822   0.161758   \n",
       "\n",
       "        period_2   period_3   period_4   period_5   period_6   period_7  \\\n",
       "count  40.000000  40.000000  40.000000  40.000000  40.000000  40.000000   \n",
       "mean    0.101724   0.085157  -0.048844  -0.007572  -0.004387  -0.069840   \n",
       "std     0.012965   0.009044   0.003392   0.004496   0.005891   0.031096   \n",
       "min     0.024470   0.032232  -0.054773  -0.015199  -0.013682  -0.109885   \n",
       "25%     0.101999   0.084409  -0.051611  -0.011199  -0.009677  -0.096453   \n",
       "50%     0.104043   0.086454  -0.048871  -0.008113  -0.005000  -0.077138   \n",
       "75%     0.106233   0.088906  -0.046090  -0.003330   0.000781  -0.049038   \n",
       "max     0.107225   0.090304  -0.039228  -0.000345   0.004865  -0.000186   \n",
       "\n",
       "       season_1996-97  season_1997-98  season_1998-99  season_1999-00  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.051563       -0.093281        0.096971        0.018851   \n",
       "std          0.010435        0.015414        0.014681        0.006959   \n",
       "min         -0.005850       -0.104881        0.010274        0.003793   \n",
       "25%          0.049071       -0.101926        0.096177        0.014333   \n",
       "50%          0.052282       -0.097806        0.100464        0.021533   \n",
       "75%          0.057059       -0.090908        0.102318        0.024399   \n",
       "max          0.060180       -0.015970        0.104036        0.025816   \n",
       "\n",
       "       season_2000-01  season_2001-02  season_2002-03  season_2003-04  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.113854        0.185078        0.161640        0.020736   \n",
       "std          0.018909        0.036185        0.031453        0.006664   \n",
       "min          0.019121        0.006977        0.004504       -0.014680   \n",
       "25%          0.112363        0.185702        0.163806        0.019724   \n",
       "50%          0.120672        0.198293        0.173212        0.021254   \n",
       "75%          0.124087        0.202959        0.176155        0.024213   \n",
       "max          0.125016        0.205374        0.177142        0.025693   \n",
       "\n",
       "       season_2004-05  season_2005-06  season_2006-07  season_2007-08  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean        -0.087354       -0.054919        0.012259        0.012480   \n",
       "std          0.026247        0.033650        0.023476        0.021789   \n",
       "min         -0.110035       -0.085255       -0.011810       -0.011245   \n",
       "25%         -0.105474       -0.079247       -0.006547       -0.005639   \n",
       "50%         -0.097101       -0.067666        0.004304        0.005608   \n",
       "75%         -0.079622       -0.043331        0.023668        0.025699   \n",
       "max         -0.000123        0.041797        0.074039        0.064187   \n",
       "\n",
       "       season_2008-09  season_2009-10  season_2010-11  season_2011-12  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.040967        0.011077        0.009685       -0.010631   \n",
       "std          0.016627        0.009775        0.005467        0.014950   \n",
       "min          0.022387       -0.001433        0.001257       -0.047676   \n",
       "25%          0.027346        0.002995        0.004779       -0.017599   \n",
       "50%          0.035283        0.008703        0.008696       -0.005398   \n",
       "75%          0.050680        0.018176        0.014497        0.000899   \n",
       "max          0.078122        0.030141        0.019069        0.003389   \n",
       "\n",
       "       season_2012-13  season_2013-14  season_2014-15  season_2015-16  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.085257        0.059069       -0.120369       -0.301187   \n",
       "std          0.021557        0.026225        0.017243        0.043101   \n",
       "min          0.012124       -0.003103       -0.131513       -0.316590   \n",
       "25%          0.077543        0.045723       -0.128036       -0.314188   \n",
       "50%          0.093725        0.069030       -0.124414       -0.311311   \n",
       "75%          0.100688        0.079714       -0.118467       -0.305469   \n",
       "max          0.103894        0.084891       -0.022226       -0.044306   \n",
       "\n",
       "       shot_type_2PT Field Goal  shot_type_3PT Field Goal  \\\n",
       "count                 40.000000                 40.000000   \n",
       "mean                   0.045509                  0.166240   \n",
       "std                    0.041318                  0.028663   \n",
       "min                   -0.009880                  0.005783   \n",
       "25%                    0.009287                  0.163842   \n",
       "50%                    0.037271                  0.171291   \n",
       "75%                    0.074938                  0.180215   \n",
       "max                    0.128527                  0.183912   \n",
       "\n",
       "       shot_zone_area_Back Court(BC)  shot_zone_area_Center(C)  \\\n",
       "count                      40.000000                 40.000000   \n",
       "mean                       -0.539157                  0.180677   \n",
       "std                         0.160596                  0.027222   \n",
       "min                        -0.711816                  0.061448   \n",
       "25%                        -0.661271                  0.175521   \n",
       "50%                        -0.586120                  0.190105   \n",
       "75%                        -0.466177                  0.197081   \n",
       "max                        -0.014778                  0.203089   \n",
       "\n",
       "       shot_zone_area_Left Side Center(LC)  shot_zone_area_Left Side(L)  \\\n",
       "count                            40.000000                    40.000000   \n",
       "mean                              0.017662                    -0.006811   \n",
       "std                               0.006668                     0.006507   \n",
       "min                               0.011437                    -0.020853   \n",
       "25%                               0.013254                    -0.011018   \n",
       "50%                               0.014719                    -0.009434   \n",
       "75%                               0.019583                    -0.003237   \n",
       "max                               0.035592                     0.007758   \n",
       "\n",
       "       shot_zone_area_Right Side Center(RC)  shot_zone_area_Right Side(R)  \\\n",
       "count                             40.000000                     40.000000   \n",
       "mean                               0.298203                      0.261174   \n",
       "std                                0.058680                      0.064817   \n",
       "min                                0.052727                     -0.010554   \n",
       "25%                                0.285053                      0.249505   \n",
       "50%                                0.319134                      0.284801   \n",
       "75%                                0.335041                      0.300857   \n",
       "max                                0.344423                      0.310619   \n",
       "\n",
       "       shot_zone_basic_Above the Break 3  shot_zone_basic_Backcourt  \\\n",
       "count                          40.000000                  40.000000   \n",
       "mean                           -0.245895                  -0.385099   \n",
       "std                             0.055024                   0.108744   \n",
       "min                            -0.286435                  -0.499688   \n",
       "25%                            -0.277639                  -0.464433   \n",
       "50%                            -0.265436                  -0.419068   \n",
       "75%                            -0.240819                  -0.340730   \n",
       "max                            -0.003460                  -0.011645   \n",
       "\n",
       "       shot_zone_basic_In The Paint (Non-RA)  shot_zone_basic_Left Corner 3  \\\n",
       "count                              40.000000                      40.000000   \n",
       "mean                                0.138121                       0.346058   \n",
       "std                                 0.039124                       0.064949   \n",
       "min                                -0.015579                       0.011332   \n",
       "25%                                 0.129136                       0.358730   \n",
       "50%                                 0.152229                       0.368996   \n",
       "75%                                 0.163235                       0.370037   \n",
       "max                                 0.169776                       0.373714   \n",
       "\n",
       "       shot_zone_basic_Mid-Range  shot_zone_basic_Restricted Area  \\\n",
       "count                  40.000000                        40.000000   \n",
       "mean                    0.059446                         0.297299   \n",
       "std                     0.019599                         0.051913   \n",
       "min                     0.002260                         0.090432   \n",
       "25%                     0.054434                         0.279390   \n",
       "50%                     0.067237                         0.314249   \n",
       "75%                     0.072860                         0.332654   \n",
       "max                     0.076516                         0.348250   \n",
       "\n",
       "       shot_zone_basic_Right Corner 3  shot_zone_range_16-24 ft.  \\\n",
       "count                       40.000000                  40.000000   \n",
       "mean                         0.001818                   0.244209   \n",
       "std                          0.029698                   0.037442   \n",
       "min                         -0.036372                   0.041882   \n",
       "25%                         -0.020639                   0.243150   \n",
       "50%                         -0.005522                   0.255806   \n",
       "75%                          0.018177                   0.261476   \n",
       "max                          0.070421                   0.265622   \n",
       "\n",
       "       shot_zone_range_24+ ft.  shot_zone_range_8-16 ft.  \\\n",
       "count                40.000000                 40.000000   \n",
       "mean                  0.256039                  0.228884   \n",
       "std                   0.040914                  0.048028   \n",
       "min                   0.015708                  0.016023   \n",
       "25%                   0.264796                  0.220317   \n",
       "50%                   0.266072                  0.245764   \n",
       "75%                   0.266692                  0.257403   \n",
       "max                   0.268473                  0.265839   \n",
       "\n",
       "       shot_zone_range_Back Court Shot  shot_zone_range_Less Than 8 ft.  \\\n",
       "count                        40.000000                        40.000000   \n",
       "mean                         -0.539157                         0.021774   \n",
       "std                           0.160596                         0.036059   \n",
       "min                          -0.711816                        -0.071123   \n",
       "25%                          -0.661271                         0.004058   \n",
       "50%                          -0.586120                         0.032146   \n",
       "75%                          -0.466177                         0.049869   \n",
       "max                          -0.014778                         0.061989   \n",
       "\n",
       "       game_year_1996  game_year_1997  game_year_1998  game_year_1999  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean        -0.065477        0.004729        0.019030        0.097155   \n",
       "std          0.020551        0.002586        0.008909        0.015141   \n",
       "min         -0.085429       -0.009142       -0.012011        0.010792   \n",
       "25%         -0.080679        0.004366        0.019465        0.094771   \n",
       "50%         -0.072947        0.005121        0.023039        0.097960   \n",
       "75%         -0.057819        0.006072        0.023685        0.104191   \n",
       "max         -0.002760        0.006781        0.024461        0.108556   \n",
       "\n",
       "       game_year_2000  game_year_2001  game_year_2002  game_year_2003  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.150650       -0.008947       -0.126750       -0.071629   \n",
       "std          0.020860        0.015009        0.028162        0.019716   \n",
       "min          0.032615       -0.024976       -0.148460       -0.087833   \n",
       "25%          0.146036       -0.021389       -0.144670       -0.084616   \n",
       "50%          0.151011       -0.014003       -0.136996       -0.079119   \n",
       "75%          0.160211       -0.000837       -0.121879       -0.067914   \n",
       "max          0.169342        0.029668       -0.012936       -0.002344   \n",
       "\n",
       "       game_year_2004  game_year_2005  game_year_2006  game_year_2007  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.001050        0.229996        0.275859        0.112411   \n",
       "std          0.004349        0.045186        0.047079        0.025115   \n",
       "min         -0.013708        0.010525        0.044983        0.017474   \n",
       "25%          0.000152        0.228383        0.273049        0.105904   \n",
       "50%          0.002959        0.246359        0.292819        0.122321   \n",
       "75%          0.003851        0.253352        0.300592        0.129650   \n",
       "max          0.004521        0.255897        0.303934        0.131761   \n",
       "\n",
       "       game_year_2008  game_year_2009  game_year_2010  game_year_2011  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean         0.096170        0.082606        0.018712        0.002069   \n",
       "std          0.016706        0.013080        0.003876        0.004744   \n",
       "min          0.031801        0.026251        0.002620       -0.004150   \n",
       "25%          0.090459        0.078808        0.017052       -0.001444   \n",
       "50%          0.102525        0.087487        0.020139        0.000933   \n",
       "75%          0.108149        0.091328        0.021316        0.003223   \n",
       "max          0.109783        0.092676        0.022240        0.017545   \n",
       "\n",
       "       game_year_2012  game_year_2013  game_year_2014  game_year_2015  \\\n",
       "count       40.000000       40.000000       40.000000       40.000000   \n",
       "mean        -0.024652       -0.159678       -0.134910       -0.081101   \n",
       "std          0.022190        0.037722        0.020683        0.009713   \n",
       "min         -0.049371       -0.192723       -0.146090       -0.085584   \n",
       "25%         -0.042871       -0.185015       -0.143501       -0.083164   \n",
       "50%         -0.031747       -0.172752       -0.140658       -0.082593   \n",
       "75%         -0.010239       -0.147921       -0.135146       -0.081690   \n",
       "max          0.024959       -0.002162       -0.019207       -0.021638   \n",
       "\n",
       "       game_year_2016  game_month_1  game_month_2  game_month_3  game_month_4  \\\n",
       "count       40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean        -0.205545      0.070159      0.041372     -0.040715     -0.025546   \n",
       "std          0.030542      0.008402      0.006438      0.010232      0.005964   \n",
       "min         -0.217943      0.031968      0.030474     -0.052270     -0.034281   \n",
       "25%         -0.215523      0.065865      0.036069     -0.048287     -0.030766   \n",
       "50%         -0.213108      0.070128      0.040012     -0.043365     -0.026241   \n",
       "75%         -0.207699      0.075909      0.046194     -0.035901     -0.020713   \n",
       "max         -0.025687      0.080735      0.054891     -0.002879     -0.007392   \n",
       "\n",
       "       game_month_5  game_month_6  game_month_10  game_month_11  \\\n",
       "count     40.000000     40.000000      40.000000      40.000000   \n",
       "mean       0.156930      0.022647      -0.018554       0.005149   \n",
       "std        0.022060      0.007123       0.006214       0.006273   \n",
       "min        0.026707     -0.009276      -0.028006      -0.003830   \n",
       "25%        0.159223      0.021503      -0.023944      -0.000012   \n",
       "50%        0.161223      0.024037      -0.019853       0.004169   \n",
       "75%        0.163679      0.026964      -0.013360       0.009577   \n",
       "max        0.165032      0.028243      -0.005955       0.019285   \n",
       "\n",
       "       game_month_12  opponent_ATL  opponent_BKN  opponent_BOS  opponent_CHA  \\\n",
       "count      40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean        0.000306     -0.018743     -0.344178     -0.039958      0.046997   \n",
       "std         0.007942      0.003287      0.102250      0.004584      0.008847   \n",
       "min        -0.010174     -0.022612     -0.434772     -0.041504      0.001895   \n",
       "25%        -0.006413     -0.019178     -0.412989     -0.040880      0.047684   \n",
       "50%        -0.001506     -0.018784     -0.382724     -0.040645      0.050196   \n",
       "75%         0.005602     -0.018551     -0.314237     -0.040455      0.050749   \n",
       "max         0.019870      0.000383     -0.002745     -0.011792      0.051429   \n",
       "\n",
       "       opponent_CHI  opponent_CLE  opponent_DAL  opponent_DEN  opponent_DET  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean       0.051972     -0.013875      0.029760      0.031328      0.063125   \n",
       "std        0.010361      0.002111      0.003608      0.002946      0.011183   \n",
       "min       -0.000746     -0.017513      0.007971      0.013580      0.001709   \n",
       "25%        0.053352     -0.014144      0.030128      0.031226      0.064856   \n",
       "50%        0.055800     -0.013725      0.030577      0.031748      0.066653   \n",
       "75%        0.056068     -0.013543      0.030703      0.032359      0.067037   \n",
       "max        0.056861     -0.002645      0.030904      0.032718      0.067543   \n",
       "\n",
       "       opponent_GSW  opponent_HOU  opponent_IND  opponent_LAC  opponent_MEM  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean      -0.056893     -0.108757     -0.074839      0.010762     -0.018047   \n",
       "std        0.010889      0.015435      0.010126      0.000903      0.002662   \n",
       "min       -0.062018     -0.112340     -0.080212      0.008113     -0.019875   \n",
       "25%       -0.060968     -0.111673     -0.078730      0.010319     -0.018640   \n",
       "50%       -0.059599     -0.111576     -0.077320      0.010843     -0.018212   \n",
       "75%       -0.057609     -0.111432     -0.074705      0.011355     -0.018018   \n",
       "max        0.005494     -0.014402     -0.015876      0.013242     -0.001949   \n",
       "\n",
       "       opponent_MIA  opponent_MIL  opponent_MIN  opponent_NJN  opponent_NOH  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean      -0.053903      0.058901      0.030095     -0.164618      0.113523   \n",
       "std        0.009065      0.014015      0.003716      0.027765      0.019086   \n",
       "min       -0.059187     -0.008700      0.007545     -0.176977      0.006654   \n",
       "25%       -0.057861      0.059576      0.030077     -0.174754      0.116347   \n",
       "50%       -0.056290      0.064058      0.030721     -0.172487      0.119318   \n",
       "75%       -0.053576      0.065370      0.031281     -0.167121      0.119940   \n",
       "max       -0.003553      0.066918      0.031701     -0.008170      0.120873   \n",
       "\n",
       "       opponent_NOP  opponent_NYK  opponent_OKC  opponent_ORL  opponent_PHI  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean       0.056353      0.221332     -0.153844     -0.039589      0.033365   \n",
       "std        0.012906      0.034533      0.023708      0.005892      0.004660   \n",
       "min       -0.002009      0.020976     -0.163294     -0.042428      0.005174   \n",
       "25%        0.056874      0.226952     -0.161628     -0.040750      0.033497   \n",
       "50%        0.061314      0.230923     -0.159934     -0.040261      0.034084   \n",
       "75%        0.062701      0.231628     -0.156531     -0.040167      0.034800   \n",
       "max        0.063678      0.232375     -0.015394     -0.003601      0.035296   \n",
       "\n",
       "       opponent_PHX  opponent_POR  opponent_SAC  opponent_SAS  opponent_SEA  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000     40.000000   \n",
       "mean       0.139102      0.048882      0.144058      0.009122      0.079894   \n",
       "std        0.018039      0.004664      0.020066      0.002829      0.011262   \n",
       "min        0.031757      0.020361      0.024663     -0.005870      0.011383   \n",
       "25%        0.141739      0.049109      0.147416      0.009644      0.081898   \n",
       "50%        0.143755      0.049711      0.149144      0.010018      0.082071   \n",
       "75%        0.144082      0.050110      0.149402      0.010159      0.082366   \n",
       "max        0.144682      0.050401      0.149935      0.010492      0.082707   \n",
       "\n",
       "       opponent_TOR  opponent_UTA  opponent_VAN  opponent_WAS  \\\n",
       "count     40.000000     40.000000     40.000000     40.000000   \n",
       "mean      -0.109594      0.043009      0.137749      0.059258   \n",
       "std        0.019087      0.006371      0.028164      0.010289   \n",
       "min       -0.117698      0.005427      0.003223      0.001633   \n",
       "25%       -0.116170      0.044023      0.138449      0.060729   \n",
       "50%       -0.114579      0.044596      0.148069      0.062519   \n",
       "75%       -0.111522      0.044832      0.151764      0.062779   \n",
       "max       -0.000525      0.045096      0.154120      0.063064   \n",
       "\n",
       "       loc_x_(-250.498, -230.08]  loc_x_(-230.08, -210.16]  \\\n",
       "count                  40.000000                 40.000000   \n",
       "mean                    0.000948                  0.206578   \n",
       "std                     0.015999                  0.042190   \n",
       "min                    -0.027085                  0.005763   \n",
       "25%                    -0.013011                  0.214670   \n",
       "50%                     0.001156                  0.222311   \n",
       "75%                     0.012374                  0.224328   \n",
       "max                     0.032141                  0.226228   \n",
       "\n",
       "       loc_x_(-210.16, -190.24]  loc_x_(-190.24, -170.32]  \\\n",
       "count                 40.000000                 40.000000   \n",
       "mean                   0.211461                  0.163798   \n",
       "std                    0.049450                  0.041436   \n",
       "min                    0.002493                  0.000302   \n",
       "25%                    0.214921                  0.163169   \n",
       "50%                    0.232898                  0.182239   \n",
       "75%                    0.234671                  0.185421   \n",
       "max                    0.240995                  0.190733   \n",
       "\n",
       "       loc_x_(-170.32, -150.4]  loc_x_(-150.4, -130.48]  \\\n",
       "count                40.000000                40.000000   \n",
       "mean                  0.175974                 0.101195   \n",
       "std                   0.040811                 0.030844   \n",
       "min                   0.006281                -0.002246   \n",
       "25%                   0.172829                 0.094156   \n",
       "50%                   0.192732                 0.113664   \n",
       "75%                   0.198659                 0.121554   \n",
       "max                   0.203314                 0.125507   \n",
       "\n",
       "       loc_x_(-130.48, -110.56]  loc_x_(-110.56, -90.64]  \\\n",
       "count                 40.000000                40.000000   \n",
       "mean                  -0.068512                 0.007018   \n",
       "std                    0.020649                 0.021834   \n",
       "min                   -0.115374                -0.041307   \n",
       "25%                   -0.078867                -0.005107   \n",
       "50%                   -0.062274                 0.013122   \n",
       "75%                   -0.053577                 0.025194   \n",
       "max                   -0.024520                 0.033160   \n",
       "\n",
       "       loc_x_(-90.64, -70.72]  loc_x_(-70.72, -50.8]  loc_x_(-50.8, -30.88]  \\\n",
       "count               40.000000              40.000000              40.000000   \n",
       "mean                 0.056858              -0.078517              -0.111587   \n",
       "std                  0.019085               0.012450               0.018233   \n",
       "min                  0.008135              -0.088423              -0.120745   \n",
       "25%                  0.043990              -0.085132              -0.119136   \n",
       "50%                  0.061916              -0.079867              -0.117135   \n",
       "75%                  0.072940              -0.076253              -0.113114   \n",
       "max                  0.081455              -0.011411              -0.015921   \n",
       "\n",
       "       loc_x_(-30.88, -10.96]  loc_x_(-10.96, 8.96]  loc_x_(8.96, 28.88]  \\\n",
       "count               40.000000             40.000000            40.000000   \n",
       "mean                -0.013268              0.057450             0.048331   \n",
       "std                  0.007026              0.011526             0.009050   \n",
       "min                 -0.019938              0.047884             0.001631   \n",
       "25%                 -0.018261              0.049943             0.044731   \n",
       "50%                 -0.014927              0.054912             0.049005   \n",
       "75%                 -0.011217              0.059141             0.052715   \n",
       "max                  0.013114              0.099564             0.061464   \n",
       "\n",
       "       loc_x_(28.88, 48.8]  loc_x_(48.8, 68.72]  loc_x_(68.72, 88.64]  \\\n",
       "count            40.000000            40.000000             40.000000   \n",
       "mean             -0.013171            -0.001099             -0.096437   \n",
       "std               0.006851             0.012877              0.033303   \n",
       "min              -0.020004            -0.011395             -0.119683   \n",
       "25%              -0.018016            -0.007514             -0.115282   \n",
       "50%              -0.014731            -0.006381             -0.111275   \n",
       "75%              -0.010908            -0.001271             -0.093784   \n",
       "max               0.011213             0.045423              0.018284   \n",
       "\n",
       "       loc_x_(88.64, 108.56]  loc_x_(108.56, 128.48]  loc_x_(128.48, 148.4]  \\\n",
       "count              40.000000               40.000000              40.000000   \n",
       "mean               -0.213162               -0.098075              -0.185397   \n",
       "std                 0.043414                0.031848               0.038640   \n",
       "min                -0.239324               -0.123433              -0.216598   \n",
       "25%                -0.235770               -0.118667              -0.209248   \n",
       "50%                -0.230214               -0.110931              -0.199105   \n",
       "75%                -0.210836               -0.090560              -0.176242   \n",
       "max                -0.013454                0.010990              -0.019620   \n",
       "\n",
       "       loc_x_(148.4, 168.32]  loc_x_(168.32, 188.24]  loc_x_(188.24, 208.16]  \\\n",
       "count              40.000000               40.000000               40.000000   \n",
       "mean               -0.110042                0.064878                0.074967   \n",
       "std                 0.029593                0.020898                0.022350   \n",
       "min                -0.141002                0.015912                0.009696   \n",
       "25%                -0.131729                0.048481                0.058296   \n",
       "50%                -0.119619                0.060952                0.073115   \n",
       "75%                -0.096743                0.081702                0.093693   \n",
       "max                -0.009579                0.100942                0.108880   \n",
       "\n",
       "       loc_x_(208.16, 228.08]  loc_x_(228.08, 248.0]  loc_y_(-44.835, -10.6]  \\\n",
       "count               40.000000              40.000000               40.000000   \n",
       "mean                -0.095597               0.127157                0.034805   \n",
       "std                  0.027549               0.024269                0.058746   \n",
       "min                 -0.137059               0.007138               -0.055769   \n",
       "25%                 -0.118652               0.118726               -0.014342   \n",
       "50%                 -0.100095               0.130059                0.039966   \n",
       "75%                 -0.075900               0.142297                0.088369   \n",
       "max                 -0.005205               0.151041                0.128460   \n",
       "\n",
       "       loc_y_(-10.6, 22.8]  loc_y_(22.8, 56.2]  loc_y_(56.2, 89.6]  \\\n",
       "count            40.000000           40.000000           40.000000   \n",
       "mean              0.096461           -0.006612            0.076793   \n",
       "std               0.061976            0.059888            0.062626   \n",
       "min              -0.002447           -0.102745           -0.027164   \n",
       "25%               0.046267           -0.055623            0.024685   \n",
       "50%               0.102938           -0.000670            0.085973   \n",
       "75%               0.152398            0.047416            0.132830   \n",
       "max               0.193428            0.087252            0.170450   \n",
       "\n",
       "       loc_y_(89.6, 123.0]  loc_y_(123.0, 156.4]  loc_y_(156.4, 189.8]  \\\n",
       "count            40.000000             40.000000             40.000000   \n",
       "mean              0.186131              0.430928              0.417530   \n",
       "std               0.069598              0.089287              0.090242   \n",
       "min               0.006561              0.070188              0.053200   \n",
       "25%               0.140289              0.394261              0.385146   \n",
       "50%               0.200701              0.454266              0.443142   \n",
       "75%               0.245014              0.495443              0.480879   \n",
       "max               0.279436              0.526268              0.507962   \n",
       "\n",
       "       loc_y_(189.8, 223.2]  loc_y_(223.2, 256.6]  loc_y_(256.6, 290.0]  \\\n",
       "count             40.000000             40.000000             40.000000   \n",
       "mean               0.378376              0.387631              0.254683   \n",
       "std                0.090397              0.098488              0.085418   \n",
       "min                0.017181             -0.003534             -0.011955   \n",
       "25%                0.351690              0.367435              0.234770   \n",
       "50%                0.406621              0.421664              0.286914   \n",
       "75%                0.439288              0.450130              0.311548   \n",
       "max                0.463546              0.471874              0.332347   \n",
       "\n",
       "       loc_y_(290.0, 323.4]  loc_y_(323.4, 356.8]  loc_y_(356.8, 390.2]  \\\n",
       "count             40.000000             40.000000             40.000000   \n",
       "mean              -0.369742              0.008790             -0.792352   \n",
       "std                0.105487              0.012109              0.343188   \n",
       "min               -0.464588             -0.020474             -1.244814   \n",
       "25%               -0.444441              0.002180             -1.085298   \n",
       "50%               -0.407969              0.013594             -0.866375   \n",
       "75%               -0.334594              0.017788             -0.563256   \n",
       "max               -0.007056              0.020305             -0.005755   \n",
       "\n",
       "       loc_y_(390.2, 423.6]  loc_y_(423.6, 457.0]  loc_y_(457.0, 490.4]  \\\n",
       "count             40.000000             40.000000             40.000000   \n",
       "mean              -0.506574              0.278369             -0.088160   \n",
       "std                0.219614              0.168393              0.034311   \n",
       "min               -0.814492             -0.000535             -0.136724   \n",
       "25%               -0.693637              0.139887             -0.116656   \n",
       "50%               -0.549317              0.294831             -0.095106   \n",
       "75%               -0.355900              0.420638             -0.065959   \n",
       "max               -0.005202              0.572149             -0.001606   \n",
       "\n",
       "       loc_y_(490.4, 523.8]  loc_y_(523.8, 557.2]  loc_y_(557.2, 590.6]  \\\n",
       "count             40.000000             40.000000             40.000000   \n",
       "mean              -0.140745             -0.054666             -0.114648   \n",
       "std                0.057512              0.022294              0.045850   \n",
       "min               -0.223031             -0.087991             -0.182277   \n",
       "25%               -0.188694             -0.073202             -0.152716   \n",
       "50%               -0.152495             -0.058833             -0.123400   \n",
       "75%               -0.102903             -0.039624             -0.084115   \n",
       "max               -0.001896             -0.001042             -0.002087   \n",
       "\n",
       "       loc_y_(590.6, 624.0]  loc_y_(624.0, 657.4]  loc_y_(657.4, 690.8]  \\\n",
       "count             40.000000             40.000000             40.000000   \n",
       "mean              -0.075653             -0.058603             -0.032135   \n",
       "std                0.030421              0.024434              0.013764   \n",
       "min               -0.121722             -0.096671             -0.054143   \n",
       "25%               -0.100834             -0.078823             -0.043472   \n",
       "50%               -0.081197             -0.062895             -0.034450   \n",
       "75%               -0.055139             -0.041781             -0.022500   \n",
       "max               -0.001392             -0.000986             -0.000533   \n",
       "\n",
       "       loc_y_(690.8, 724.2]  loc_y_(724.2, 757.6]  loc_y_(757.6, 791.0]  \n",
       "count             40.000000             40.000000             40.000000  \n",
       "mean              -0.045107             -0.031875             -0.021876  \n",
       "std                0.019109              0.013882              0.009686  \n",
       "min               -0.076084             -0.054854             -0.038340  \n",
       "25%               -0.060758             -0.043201             -0.029732  \n",
       "50%               -0.048215             -0.034031             -0.023276  \n",
       "75%               -0.031736             -0.021985             -0.014875  \n",
       "max               -0.000718             -0.000508             -0.000340  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Таблица статистических показателей для признаков с L2-регуляризацией')\n",
    "df_l2.T.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(c_values, df_l1.T.last_5_sec_in_period.abs(), label='l1-регуляризация')\n",
    "plt.plot(c_values, df_l2.T.last_5_sec_in_period.abs(), label='l2-регуляризация')\n",
    "plt.title('Зависимость размера веса признака last_5_sec_in_period от коэфициента регуляризации')\n",
    "plt.xlabel('Размер коэффициента С')\n",
    "plt.ylabel('Размер веса')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Из графика видно, что l2-регуляризация дает немного меньший размер весов.\n",
    "\n",
    "Разделим выборку на обучающую и тестовую, обучим логистическую регрессию с L1- и L2- регуляризацией."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y, random_state=42)\n",
    "                                                            \n",
    "scaler = StandardScaler()\n",
    "scaler.fit(X_train)\n",
    "X_train_std = scaler.transform(X_train)\n",
    "X_test_std = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=0.3, solver='liblinear')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_l1 = LogisticRegression(penalty='l1', C=0.3, solver='liblinear')\n",
    "lr_l1.fit(X_train_std, y_train)\n",
    "\n",
    "lr_l2 = LogisticRegression(penalty='l2', C=0.3, solver='liblinear')\n",
    "lr_l2.fit(X_train_std, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Построим ROC-кривую для наших моделей."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "fpr_l1, tpr_l1, thr_l1 = roc_curve(y_test, lr_l1.predict_proba(X_test)[:,1])\n",
    "fpr_l2, tpr_l2, thr_l1 = roc_curve(y_test, lr_l2.predict_proba(X_test)[:,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(fpr_l1, tpr_l1, label='L1-регуляризация')\n",
    "plt.plot(fpr_l2, tpr_l2, label='L2-регуляризация')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Обе модели имеют низкое качество с текущими параметрами регулязирации.\n",
    "\n",
    "Теперь попробуем сжать признаки с помощью PCA и посмотреть распределение дисперсии по главным компонентам.\n",
    "\n",
    "Методом подбора кол-ва компонент определяем, что 160 главных компонент объясняют более 98% дисперсии данных."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PCA(n_components=160)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca = PCA(n_components=160)\n",
    "pca.fit(X_train_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9833479154946022"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(pca.explained_variance_ratio_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp_ratio_cumm = np.cumsum(pca.explained_variance_ratio_ * 100)\n",
    "plt.figure(figsize=(20,5))\n",
    "plt.plot(range(1, 161), exp_ratio_cumm)\n",
    "plt.title('Увеличение % описываемой дисперсии главных компонент в зависимости от их количества')\n",
    "plt.xlabel('Кол-во главных компонент')\n",
    "plt.ylabel('% описываемой дисперсии исходных данных')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Как видно из графика каждая главная компонента объясняет небольшую часть дисперсии исходных данных и нет сильного перевеса в сторону нескольких первых главных компонент. Чтобы объяснить 98% данных нам потребовалось 160 главных компонент. При этом исходное количество признаков - 208."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
